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Henry B, Merz M, Hoang H, Abdulkarim G, Wosik J, Schoettker P. Cuffless Blood Pressure in clinical practice: challenges, opportunities and current limits. Blood Press 2024; 33:2304190. [PMID: 38245864 DOI: 10.1080/08037051.2024.2304190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/07/2024] [Indexed: 01/22/2024]
Abstract
Background: Cuffless blood pressure measurement technologies have attracted significant attention for their potential to transform cardiovascular monitoring.Methods: This updated narrative review thoroughly examines the challenges, opportunities, and limitations associated with the implementation of cuffless blood pressure monitoring systems.Results: Diverse technologies, including photoplethysmography, tonometry, and ECG analysis, enable cuffless blood pressure measurement and are integrated into devices like smartphones and smartwatches. Signal processing emerges as a critical aspect, dictating the accuracy and reliability of readings. Despite its potential, the integration of cuffless technologies into clinical practice faces obstacles, including the need to address concerns related to accuracy, calibration, and standardization across diverse devices and patient populations. The development of robust algorithms to mitigate artifacts and environmental disturbances is essential for extracting clear physiological signals. Based on extensive research, this review emphasizes the necessity for standardized protocols, validation studies, and regulatory frameworks to ensure the reliability and safety of cuffless blood pressure monitoring devices and their implementation in mainstream medical practice. Interdisciplinary collaborations between engineers, clinicians, and regulatory bodies are crucial to address technical, clinical, and regulatory complexities during implementation. In conclusion, while cuffless blood pressure monitoring holds immense potential to transform cardiovascular care. The resolution of existing challenges and the establishment of rigorous standards are imperative for its seamless incorporation into routine clinical practice.Conclusion: The emergence of these new technologies shifts the paradigm of cardiovascular health management, presenting a new possibility for non-invasive continuous and dynamic monitoring. The concept of cuffless blood pressure measurement is viable and more finely tuned devices are expected to enter the market, which could redefine our understanding of blood pressure and hypertension.
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Affiliation(s)
- Benoit Henry
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Maxime Merz
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Harry Hoang
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ghaith Abdulkarim
- Neuro-Informatics Laboratory, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
- Department of Neurological Surgery, Mayo Clinic, Rochester, MN, USA
| | - Jedrek Wosik
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Patrick Schoettker
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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2
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Yao C, Sun T, Huang S, He M, Liang B, Shen Z, Huang X, Liu Z, Wang H, Liu F, Chen HJ, Xie X. Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring. ACS NANO 2023; 17:24242-24258. [PMID: 37983291 DOI: 10.1021/acsnano.3c09766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since the correlations of pulse waveforms to BP are highly individualized due to the diversity of the patients' physiological characteristics, wearable sensors based on universal designs and algorithms often fail to derive BP accurately when applied on individual patients. Herein, a wearable triboelectric pulse sensor based on a biomimetic nanopillar layer was developed and coupled with Personalized Machine Learning (ML) to provide accurate and continuous monitoring of BP. Flexible conductive nanopillars as the triboelectric layer were fabricated through soft lithography replication of a cicada wing, which could effectively enhance the sensor's output performance to detect weak signal characteristics of pulse waveform for BP derivation. The sensors were coupled with a personalized Partial Least-Squares Regression (PLSR) ML to derive unknown BP based on individual pulse characteristics with reasonable accuracy, avoiding the issue of individual variability that was encountered by General PLSR ML or formula algorithms. The cuffless and intelligent design endow this ML-sensor as a highly promising platform for the care and treatments of hypertensive patients.
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Affiliation(s)
- Chuanjie Yao
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Tiancheng Sun
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Shuang Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Mengyi He
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Baoming Liang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Zhiran Shen
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Xinshuo Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Zhengjie Liu
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - HaoLin Wang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Fanmao Liu
- The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou 510080, China
| | - Hui-Jiuan Chen
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
| | - Xi Xie
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
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3
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Stergiou GS, Avolio AP, Palatini P, Kyriakoulis KG, Schutte AE, Mieke S, Kollias A, Parati G, Asmar R, Pantazis N, Stamoulopoulos A, Asayama K, Castiglioni P, De La Sierra A, Hahn JO, Kario K, McManus RJ, Myers M, Ohkubo T, Shroff SG, Tan I, Wang J, Zhang Y, Kreutz R, O'Brien E, Mukkamala R. European Society of Hypertension recommendations for the validation of cuffless blood pressure measuring devices: European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability. J Hypertens 2023; 41:2074-2087. [PMID: 37303198 DOI: 10.1097/hjh.0000000000003483] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND There is intense effort to develop cuffless blood pressure (BP) measuring devices, and several are already on the market claiming that they provide accurate measurements. These devices are heterogeneous in measurement principle, intended use, functions, and calibration, and have special accuracy issues requiring different validation than classic cuff BP monitors. To date, there are no generally accepted protocols for their validation to ensure adequate accuracy for clinical use. OBJECTIVE This statement by the European Society of Hypertension (ESH) Working Group on BP Monitoring and Cardiovascular Variability recommends procedures for validating intermittent cuffless BP devices (providing measurements every >30 sec and usually 30-60 min, or upon user initiation), which are most common. VALIDATION PROCEDURES Six validation tests are defined for evaluating different aspects of intermittent cuffless devices: static test (absolute BP accuracy); device position test (hydrostatic pressure effect robustness); treatment test (BP decrease accuracy); awake/asleep test (BP change accuracy); exercise test (BP increase accuracy); and recalibration test (cuff calibration stability over time). Not all these tests are required for a given device. The necessary tests depend on whether the device requires individual user calibration, measures automatically or manually, and takes measurements in more than one position. CONCLUSION The validation of cuffless BP devices is complex and needs to be tailored according to their functions and calibration. These ESH recommendations present specific, clinically meaningful, and pragmatic validation procedures for different types of intermittent cuffless devices to ensure that only accurate devices will be used in the evaluation and management of hypertension.
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Affiliation(s)
- George S Stergiou
- Hypertension Center STRIDE-7, National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, Athens, Greece
| | - Alberto P Avolio
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Paolo Palatini
- Department of Medicine, University of Padova, Padova, Italy
| | - Konstantinos G Kyriakoulis
- Hypertension Center STRIDE-7, National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, Athens, Greece
| | - Aletta E Schutte
- School of Population Health, University of New South Wales, The George Institute for Global Health, Sydney, New South Wales, Australia
| | - Stephan Mieke
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | - Anastasios Kollias
- Hypertension Center STRIDE-7, National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, Athens, Greece
| | - Gianfranco Parati
- Department of Medicine and Surgery, University of Milano-Bicocca
- Istituto Auxologico Italiano, IRCCS, Cardiology Unit and Department of Cardiovascular, Neural and Metabolic Sciences, S. Luca Hospital, Milan, Italy
| | - Roland Asmar
- Foundation-Medical Research Institutes, Geneva, Switzerland
| | - Nikos Pantazis
- Department of Hygiene, Epidemiology & Medical Statistics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Achilleas Stamoulopoulos
- Department of Hygiene, Epidemiology & Medical Statistics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Kei Asayama
- Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan
| | - Paolo Castiglioni
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy; Department of Biotechnology and Life Sciences (DBSV), University of Insubria, Varese, Italy
| | - Alejandro De La Sierra
- Department of Internal Medicine, Hospital Mutua Terrassa, University of Barcelona, Catalonia, Spain
| | - Jin-Oh Hahn
- Department of Mechanical Engineering, University of Maryland, College Park, Maryland, USA
| | - Kazuomi Kario
- Division of Cardiovascular Medicine, Department of Medicine, Jichi Medical University School of Medicine, Tochigi, Japan
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Martin Myers
- Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Takayoshi Ohkubo
- Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan
| | - Sanjeev G Shroff
- Department of Bioengineering and Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Isabella Tan
- The George Institute for Global Health, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Jiguang Wang
- The Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai
| | - Yuanting Zhang
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Reinhold Kreutz
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Department of Clinical Pharmacology & Toxicology, Charité University Medicine, Berlin, Germany
| | - Eoin O'Brien
- The Conway Institute, University College Dublin, Dublin, Ireland
| | - Ramakrishna Mukkamala
- Department of Bioengineering and Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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4
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Li J, Jia H, Zhou J, Huang X, Xu L, Jia S, Gao Z, Yao K, Li D, Zhang B, Liu Y, Huang Y, Hu Y, Zhao G, Xu Z, Li J, Yiu CK, Gao Y, Wu M, Jiao Y, Zhang Q, Tai X, Chan RH, Zhang Y, Ma X, Yu X. Thin, soft, wearable system for continuous wireless monitoring of artery blood pressure. Nat Commun 2023; 14:5009. [PMID: 37591881 PMCID: PMC10435523 DOI: 10.1038/s41467-023-40763-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 08/07/2023] [Indexed: 08/19/2023] Open
Abstract
Continuous monitoring of arterial blood pressure (BP) outside of a clinical setting is crucial for preventing and diagnosing hypertension related diseases. However, current continuous BP monitoring instruments suffer from either bulky systems or poor user-device interfacial performance, hampering their applications in continuous BP monitoring. Here, we report a thin, soft, miniaturized system (TSMS) that combines a conformal piezoelectric sensor array, an active pressure adaptation unit, a signal processing module, and an advanced machine learning method, to allow real wearable, continuous wireless monitoring of ambulatory artery BP. By optimizing the materials selection, control/sampling strategy, and system integration, the TSMS exhibits improved interfacial performance while maintaining Grade A level measurement accuracy. Initial trials on 87 volunteers and clinical tracking of two hypertension individuals prove the capability of the TSMS as a reliable BP measurement product, and its feasibility and practical usability in precise BP control and personalized diagnosis schemes development.
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Affiliation(s)
- Jian Li
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Huiling Jia
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Jingkun Zhou
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Xingcan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Long Xu
- School of Mechanical and Aerospace Engineering, Jilin University, 130012, Changchun, China
| | - Shengxin Jia
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Zhan Gao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Kuanming Yao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Dengfeng Li
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Binbin Zhang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Yiming Liu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Ya Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Yue Hu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Guangyao Zhao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Zitong Xu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Jiyu Li
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Chun Ki Yiu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Yuyu Gao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Mengge Wu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China (UESTC), 610054, Chengdu, China
| | - Yanli Jiao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Qiang Zhang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Xuecheng Tai
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
- Department of Mathematics, Hong Kong Baptist University, Hong Kong, China
| | - Raymond H Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Yuanting Zhang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Xiaohui Ma
- Department of vascular and endovascular surgery, The first medical center of Chinese PLA General Hospital, 100853, Beijing, China.
| | - Xinge Yu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China.
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China.
- City University of Hong Kong Shenzhen Research Institute, 518057, Shenzhen, China.
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5
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Sel K, Mohammadi A, Pettigrew RI, Jafari R. Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation. NPJ Digit Med 2023; 6:110. [PMID: 37296218 DOI: 10.1038/s41746-023-00853-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/24/2023] [Indexed: 06/12/2023] Open
Abstract
The bold vision of AI-driven pervasive physiological monitoring, through the proliferation of off-the-shelf wearables that began a decade ago, has created immense opportunities to extract actionable information for precision medicine. These AI algorithms model input-output relationships of a system that, in many cases, exhibits complex nature and personalization requirements. A particular example is cuffless blood pressure estimation using wearable bioimpedance. However, these algorithms need training over significant amount of ground truth data. In the context of biomedical applications, collecting ground truth data, particularly at the personalized level is challenging, burdensome, and in some cases infeasible. Our objective is to establish physics-informed neural network (PINN) models for physiological time series data that would use minimal ground truth information to extract complex cardiovascular information. We achieve this by building Taylor's approximation for gradually changing known cardiovascular relationships between input and output (e.g., sensor measurements to blood pressure) and incorporating this approximation into our proposed neural network training. The effectiveness of the framework is demonstrated through a case study: continuous cuffless BP estimation from time series bioimpedance data. We show that by using PINNs over the state-of-the-art time series models tested on the same datasets, we retain high correlations (systolic: 0.90, diastolic: 0.89) and low error (systolic: 1.3 ± 7.6 mmHg, diastolic: 0.6 ± 6.4 mmHg) while reducing the amount of ground truth training data on average by a factor of 15. This could be helpful in developing future AI algorithms to help interpret pervasive physiologic data using minimal amount of training data.
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Affiliation(s)
- Kaan Sel
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Amirmohammad Mohammadi
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | | | - Roozbeh Jafari
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.
- School of Engineering Medicine, Texas A&M University, Houston, TX, USA.
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6
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Zhao L, Liang C, Huang Y, Zhou G, Xiao Y, Ji N, Zhang YT, Zhao N. Emerging sensing and modeling technologies for wearable and cuffless blood pressure monitoring. NPJ Digit Med 2023; 6:93. [PMID: 37217650 DOI: 10.1038/s41746-023-00835-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 05/05/2023] [Indexed: 05/24/2023] Open
Abstract
Cardiovascular diseases (CVDs) are a leading cause of death worldwide. For early diagnosis, intervention and management of CVDs, it is highly desirable to frequently monitor blood pressure (BP), a vital sign closely related to CVDs, during people's daily life, including sleep time. Towards this end, wearable and cuffless BP extraction methods have been extensively researched in recent years as part of the mobile healthcare initiative. This review focuses on the enabling technologies for wearable and cuffless BP monitoring platforms, covering both the emerging flexible sensor designs and BP extraction algorithms. Based on the signal type, the sensing devices are classified into electrical, optical, and mechanical sensors, and the state-of-the-art material choices, fabrication methods, and performances of each type of sensor are briefly reviewed. In the model part of the review, contemporary algorithmic BP estimation methods for beat-to-beat BP measurements and continuous BP waveform extraction are introduced. Mainstream approaches, such as pulse transit time-based analytical models and machine learning methods, are compared in terms of their input modalities, features, implementation algorithms, and performances. The review sheds light on the interdisciplinary research opportunities to combine the latest innovations in the sensor and signal processing research fields to achieve a new generation of cuffless BP measurement devices with improved wearability, reliability, and accuracy.
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Affiliation(s)
- Lei Zhao
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Cunman Liang
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Yan Huang
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Guodong Zhou
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Yiqun Xiao
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Nan Ji
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Yuan-Ting Zhang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Ni Zhao
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China.
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China.
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7
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Ma G, Zhang J, Liu J, Wang L, Yu Y. A Multi-Parameter Fusion Method for Cuffless Continuous Blood Pressure Estimation Based on Electrocardiogram and Photoplethysmogram. MICROMACHINES 2023; 14:804. [PMID: 37421037 DOI: 10.3390/mi14040804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 07/09/2023]
Abstract
Blood pressure (BP) is an essential physiological indicator to identify and determine health status. Compared with the isolated BP measurement conducted by traditional cuff approaches, cuffless BP monitoring can reflect the dynamic changes in BP values and is more helpful to evaluate the effectiveness of BP control. In this paper, we designed a wearable device for continuous physiological signal acquisition. Based on the collected electrocardiogram (ECG) and photoplethysmogram (PPG), we proposed a multi-parameter fusion method for noninvasive BP estimation. An amount of 25 features were extracted from processed waveforms and Gaussian copula mutual information (MI) was introduced to reduce feature redundancy. After feature selection, random forest (RF) was trained to realize systolic BP (SBP) and diastolic BP (DBP) estimation. Moreover, we used the records in public MIMIC-III as the training set and private data as the testing set to avoid data leakage. The mean absolute error (MAE) and standard deviation (STD) for SBP and DBP were reduced from 9.12 ± 9.83 mmHg and 8.31 ± 9.23 mmHg to 7.93 ± 9.12 mmHg and 7.63 ± 8.61 mmHg by feature selection. After calibration, the MAE was further reduced to 5.21 mmHg and 4.15 mmHg. The result showed that MI has great potential in feature selection during BP prediction and the proposed multi-parameter fusion method can be used for long-term BP monitoring.
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Affiliation(s)
- Gang Ma
- School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Suzhou Institute of Biomedical Engineering and Technology, China Academy of Sciences, Suzhou 215163, China
| | - Jie Zhang
- Suzhou Institute of Biomedical Engineering and Technology, China Academy of Sciences, Suzhou 215163, China
| | - Jing Liu
- School of Electronics and Information Technology, Soochow University, Suzhou 215031, China
| | - Lirong Wang
- Suzhou Institute of Biomedical Engineering and Technology, China Academy of Sciences, Suzhou 215163, China
- School of Electronics and Information Technology, Soochow University, Suzhou 215031, China
| | - Yong Yu
- Suzhou Institute of Biomedical Engineering and Technology, China Academy of Sciences, Suzhou 215163, China
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8
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Sel K, Osman D, Huerta N, Edgar A, Pettigrew RI, Jafari R. Continuous cuffless blood pressure monitoring with a wearable ring bioimpedance device. NPJ Digit Med 2023; 6:59. [PMID: 36997608 PMCID: PMC10063561 DOI: 10.1038/s41746-023-00796-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 03/10/2023] [Indexed: 04/01/2023] Open
Abstract
Smart rings provide unique opportunities for continuous physiological measurement. They are easy to wear, provide little burden in comparison to other smart wearables, are suitable for nocturnal settings, and can be sized to provide ideal contact between the sensors and the skin at all times. Continuous measuring of blood pressure (BP) provides essential diagnostic and prognostic value for cardiovascular health management. However, conventional ambulatory BP measurement devices operate using an inflating cuff that is bulky, intrusive, and impractical for frequent or continuous measurements. We introduce ring-shaped bioimpedance sensors leveraging the deep tissue sensing ability of bioimpedance while introducing no sensitivity to skin tones, unlike optical modalities. We integrate unique human finger finite element model with exhaustive experimental data from participants and derive optimum design parameters for electrode placement and sizes that yields highest sensitivity to arterial volumetric changes, with no discrimination against varying skin tones. BP is constructed using machine learning algorithms. The ring sensors are used to estimate arterial BP showing peak correlations of 0.81, and low error (systolic BP: 0.11 ± 5.27 mmHg, diastolic BP: 0.11 ± 3.87 mmHg) for >2000 data points and wide BP ranges (systolic: 89-213 mmHg and diastolic: 42-122 mmHg), highlighting the significant potential use of bioimpedance ring for accurate and continuous estimation of BP.
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Affiliation(s)
- Kaan Sel
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Deen Osman
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Noah Huerta
- Department of Mechanical Engineering, Texas A&M University, College Station, TX, USA
| | - Arabella Edgar
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | | | - Roozbeh Jafari
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA.
- School of Engineering Medicine, Texas A&M University, Houston, TX, USA.
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.
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9
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Nour M, Polat K, Şentürk Ü, Arıcan M. A Novel Cuffless Blood Pressure Prediction: Uncovering New Features and New Hybrid ML Models. Diagnostics (Basel) 2023; 13:diagnostics13071278. [PMID: 37046499 PMCID: PMC10093721 DOI: 10.3390/diagnostics13071278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/15/2023] [Accepted: 03/23/2023] [Indexed: 03/31/2023] Open
Abstract
This paper investigates new feature extraction and regression methods for predicting cuffless blood pressure from PPG signals. Cuffless blood pressure is a technology that measures blood pressure without needing a cuff. This technology can be used in various medical applications, including home health monitoring, clinical uses, and portable devices. The new feature extraction method involves extracting meaningful features (time and chaotic features) from the PPG signals in the prediction of systolic blood pressure (SBP) and diastolic blood pressure (DBP) values. These extracted features are then used as inputs to regression models, which are used to predict cuffless blood pressure. The regression model performances were evaluated using root mean squared error (RMSE), R2, mean square error (MSE), and the mean absolute error (MAE). The obtained RMSE was 4.277 for systolic blood pressure (SBP) values using the Matérn 5/2 Gaussian process regression model. The obtained RMSE was 2.303 for diastolic blood pressure (DBP) values using the rational quadratic Gaussian process regression model. The results of this study have shown that the proposed feature extraction and regression models can predict cuffless blood pressure with reasonable accuracy. This study provides a novel approach for predicting cuffless blood pressure and can be used to develop more accurate models in the future.
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Affiliation(s)
- Majid Nour
- Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Kemal Polat
- Department of Electrical and Electronics Engineering, Faculty of Engineering, Bolu Abant Izzet Baysal University, 14280 Bolu, Turkey
- Correspondence:
| | - Ümit Şentürk
- Department of Computer Engineering, Faculty of Engineering, Bolu Abant Izzet Baysal University, 14280 Bolu, Turkey
| | - Murat Arıcan
- Department of Electrical and Electronics Engineering, Faculty of Engineering, Bolu Abant Izzet Baysal University, 14280 Bolu, Turkey
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10
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Deng Z, Guo L, Chen X, Wu W. Smart Wearable Systems for Health Monitoring. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23052479. [PMID: 36904682 PMCID: PMC10007426 DOI: 10.3390/s23052479] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/19/2023] [Accepted: 02/21/2023] [Indexed: 06/12/2023]
Abstract
Smart wearable systems for health monitoring are highly desired in personal wisdom medicine and telemedicine. These systems make the detecting, monitoring, and recording of biosignals portable, long-term, and comfortable. The development and optimization of wearable health-monitoring systems have focused on advanced materials and system integration, and the number of high-performance wearable systems has been gradually increasing in recent years. However, there are still many challenges in these fields, such as balancing the trade-off between flexibility/stretchability, sensing performance, and the robustness of systems. For this reason, more evolution is required to promote the development of wearable health-monitoring systems. In this regard, this review summarizes some representative achievements and recent progress of wearable systems for health monitoring. Meanwhile, a strategy overview is presented about selecting materials, integrating systems, and monitoring biosignals. The next generation of wearable systems for accurate, portable, continuous, and long-term health monitoring will offer more opportunities for disease diagnosis and treatment.
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Affiliation(s)
- Zhiyong Deng
- School of Nuclear Science and Technology, Lanzhou University, Lanzhou 730000, China
- Nuclear Power Institute of China, Huayang, Shuangliu District, Chengdu 610213, China
| | - Lihao Guo
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
| | - Ximeng Chen
- School of Nuclear Science and Technology, Lanzhou University, Lanzhou 730000, China
| | - Weiwei Wu
- School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Xi’an 710126, China
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11
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Sel K, Mohammadi A, Pettigrew RI, Jafari R. Physics-Informed Neural Networks for Modeling Physiological Time Series: A Case Study with Continuous Blood Pressure. RESEARCH SQUARE 2023:rs.3.rs-2423200. [PMID: 36711741 PMCID: PMC9882661 DOI: 10.21203/rs.3.rs-2423200/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The bold vision of AI-driven pervasive physiological monitoring, through the proliferation of off-the-shelf wearables that began a decade ago, has created immense opportunities to extract actionable information for precision medicine. These AI algorithms model the input-output relationships of a system that, in many cases, exhibits complex nature and personalization requirements. A particular example is cuffless blood pressure estimation using wearable bioimpedance. However, these algorithms need to be trained with a significant amount of ground truth data. In the context of biomedical applications, collecting ground truth data, particularly at the personalized level is challenging, burdensome, and in some cases infeasible. Our objective is to establish physics-informed neural network (PINN) models for physiological time series data that would reduce reliance on ground truth information. We achieve this by building Taylor's approximation for the gradually changing known cardiovascular relationships between input and output (e.g., sensor measurements to blood pressure) and incorporating this approximation into our proposed neural network training. The effectiveness of the framework is demonstrated through a case study: continuous cuffless BP estimation from time series bioimpedance data. We show that by using PINNs over the state-of-the-art time series regression models tested on the same datasets, we retain a high correlation (systolic: 0.90, diastolic: 0.89) and low error (systolic: 1.3 ± 7.6 mmHg, diastolic: 0.6 ± 6.4 mmHg) while reducing the amount of ground truth training data on average by a factor of 15. This could be helpful in developing future AI algorithms to help interpret pervasive physiologic data using minimal amount of training data.
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Affiliation(s)
- Kaan Sel
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Amirmohammad Mohammadi
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | | | - Roozbeh Jafari
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA,Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA,School of Engineering Medicine, Texas A&M University, Houston, TX, USA,Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA,corresponding author:
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12
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Long-term stability of over-the-counter cuffless blood pressure monitors: a proposal. HEALTH AND TECHNOLOGY 2023; 13:53-63. [PMID: 36713070 PMCID: PMC9870659 DOI: 10.1007/s12553-023-00726-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 10/17/2022] [Accepted: 01/04/2023] [Indexed: 01/25/2023]
Abstract
Blood pressure is an important cardiovascular parameter. Currently, the cuff-based sphygmomanometer is a popular, reliable, measurement method, but blood pressure monitors without cuffs have become popular and are now available without a prescription. Blood pressure monitors must be approved by regulatory authorities. Current cuffless blood pressure (CL-BP) monitors are not suitable for at-home management and prevention of hypertension. This paper proposes simple criteria for over-the-counter CL-BP monitoring. First, the history of the sphygmomanometer and current standard blood pressure protocol are reviewed. The main components of CL-BP monitoring are accuracy during the resting condition, accuracy during dynamic blood pressure changes, and long-term stability. In this proposal we recommend intermittent measurement to ensure that active measurement accuracy mirrors resting condition accuracy. A new experimental protocol is proposed to maintain long-term stability. A medically approved automated sphygmomanometer was used as the standard device in this study. The long-term accuracy of the test device is based on the definition of propagation error, i.e., for an oscillometric automated sphygmomanometer (5 ± 8 mmHg) ± the error for the test device static accuracy (-0.12 ± 5.49 mmHg for systolic blood pressure and - 1.17 ± 5.06 mmHg for diastolic blood pressure). Thus, the long-term stabilities were - 3.38 ± 7.1 mmHg and - 1.38 ± 5.4 mmHg, which satisfied propagation error. Further research and discussion are necessary to create standards for use by manufacturers; such standards should be readily evaluated and ensure high-quality evidence. Supplementary information The online version contains supplementary material available at 10.1007/s12553-023-00726-6.
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Khan Mamun MMR, Sherif A. Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 10:bioengineering10010027. [PMID: 36671599 PMCID: PMC9854981 DOI: 10.3390/bioengineering10010027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 12/28/2022]
Abstract
Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper treatment, undesirable outcomes can be avoided. Until now, the gold standard is the invasive way of measuring blood pressure (BP) using a catheter. Additionally, the cuff-based and noninvasive methods are too cumbersome or inconvenient for frequent measurement of BP. With the advancement of sensor technology, signal processing techniques, and machine learning algorithms, researchers are trying to find the perfect relationships between biomedical signals and changes in BP. This paper is a literature review of the studies conducted on the cuffless noninvasive measurement of BP using biomedical signals. Relevant articles were selected using specific criteria, then traditional techniques for BP measurement were discussed along with a motivation for cuffless measurement use of biomedical signals and machine learning algorithms. The review focused on the progression of different noninvasive cuffless techniques rather than comparing performance among different studies. The literature survey concluded that the use of deep learning proved to be the most accurate among all the cuffless measurement techniques. On the other side, this accuracy has several disadvantages, such as lack of interpretability, computationally extensive, standard validation protocol, and lack of collaboration with health professionals. Additionally, the continuing work by researchers is progressing with a potential solution for these challenges. Finally, future research directions have been provided to encounter the challenges.
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Affiliation(s)
| | - Ahmed Sherif
- School of Computing Sciences and Computer Engineering, The University of Southern Mississippi, Hattiesburg, MS 39406, USA
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14
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Fleischhauer V, Feldheiser A, Zaunseder S. Beat-to-Beat Blood Pressure Estimation by Photoplethysmography and Its Interpretation. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22187037. [PMID: 36146386 PMCID: PMC9506534 DOI: 10.3390/s22187037] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/29/2022] [Accepted: 09/13/2022] [Indexed: 05/28/2023]
Abstract
Blood pressure (BP) is among the most important vital signals. Estimation of absolute BP solely using photoplethysmography (PPG) has gained immense attention over the last years. Available works differ in terms of used features as well as classifiers and bear large differences in their results. This work aims to provide a machine learning method for absolute BP estimation, its interpretation using computational methods and its critical appraisal in face of the current literature. We used data from three different sources including 273 subjects and 259,986 single beats. We extracted multiple features from PPG signals and its derivatives. BP was estimated by xgboost regression. For interpretation we used Shapley additive values (SHAP). Absolute systolic BP estimation using a strict separation of subjects yielded a mean absolute error of 9.456mmHg and correlation of 0.730. The results markedly improve if data separation is changed (MAE: 6.366mmHg, r: 0.874). Interpretation by means of SHAP revealed four features from PPG, its derivation and its decomposition to be most relevant. The presented approach depicts a general way to interpret multivariate prediction algorithms and reveals certain features to be valuable for absolute BP estimation. Our work underlines the considerable impact of data selection and of training/testing separation, which must be considered in detail when algorithms are to be compared. In order to make our work traceable, we have made all methods available to the public.
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Affiliation(s)
- Vincent Fleischhauer
- Faculty of Information Technology, University of Applied Sciences and Arts Dortmund, 44139 Dortmund, Germany
- TU Dresden, Institute for Biomedical Engineering, 01069 Dresden, Germany
| | - Aarne Feldheiser
- Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Evang. Kliniken Essen-Mitte, Huyssens-Stiftung/Knappschaft, 45136 Essen, Germany
- Department of Anaesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 13353 Berlin, Germany
| | - Sebastian Zaunseder
- Faculty of Information Technology, University of Applied Sciences and Arts Dortmund, 44139 Dortmund, Germany
- TU Dresden, Institute for Biomedical Engineering, 01069 Dresden, Germany
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15
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Kireev D, Sel K, Ibrahim B, Kumar N, Akbari A, Jafari R, Akinwande D. Continuous cuffless monitoring of arterial blood pressure via graphene bioimpedance tattoos. NATURE NANOTECHNOLOGY 2022; 17:864-870. [PMID: 35725927 DOI: 10.1038/s41565-022-01145-w] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 05/03/2022] [Indexed: 05/15/2023]
Abstract
Continuous monitoring of arterial blood pressure (BP) in non-clinical (ambulatory) settings is essential for understanding numerous health conditions, including cardiovascular diseases. Besides their importance in medical diagnosis, ambulatory BP monitoring platforms can advance disease correlation with individual behaviour, daily habits and lifestyle, potentially enabling analysis of root causes, prognosis and disease prevention. Although conventional ambulatory BP devices exist, they are uncomfortable, bulky and intrusive. Here we introduce a wearable continuous BP monitoring platform that is based on electrical bioimpedance and leverages atomically thin, self-adhesive, lightweight and unobtrusive graphene electronic tattoos as human bioelectronic interfaces. The graphene electronic tattoos are used to monitor arterial BP for >300 min, a period tenfold longer than reported in previous studies. The BP is recorded continuously and non-invasively, with an accuracy of 0.2 ± 4.5 mm Hg for diastolic pressures and 0.2 ± 5.8 mm Hg for systolic pressures, a performance equivalent to Grade A classification.
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Affiliation(s)
- Dmitry Kireev
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
- Microelectronics Research Center, The University of Texas, Austin, TX, USA
| | - Kaan Sel
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Bassem Ibrahim
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Neelotpala Kumar
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Ali Akbari
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | - Roozbeh Jafari
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA.
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.
| | - Deji Akinwande
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA.
- Microelectronics Research Center, The University of Texas, Austin, TX, USA.
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16
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Falter M, Scherrenberg M, Driesen K, Pieters Z, Kaihara T, Xu L, Caiani EG, Castiglioni P, Faini A, Parati G, Dendale P. Smartwatch-Based Blood Pressure Measurement Demonstrates Insufficient Accuracy. Front Cardiovasc Med 2022; 9:958212. [PMID: 35898281 PMCID: PMC9309348 DOI: 10.3389/fcvm.2022.958212] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 06/23/2022] [Indexed: 11/13/2022] Open
Abstract
Background Novel smartwatch-based cuffless blood pressure (BP) measuring devices are coming to market and receive FDA and CE labels. These devices are often insufficiently validated for clinical use. This study aims to investigate a recently CE-cleared smartwatch using cuffless BP measurement in a population with normotensive and hypertensive individuals scheduled for 24-h BP measurement. Methods Patients that were scheduled for 24-h ambulatory blood pressure monitoring (ABPM) were recruited and received an additional Samsung Galaxy Watch Active 2 smartwatch for simultaneous BP measurement on their opposite arm. After calibration, patients were asked to measure as much as possible in a 24-h period. Manual activation of the smartwatch is necessary to measure the BP. Accuracy was calculated using sensitivity, specificity, positive and negative predictive values and ROC curves. Bland-Altman method and Taffé methods were used for bias and precision assessment. BP variability was calculated using average real variability, standard deviation and coefficient of variation. Results Forty patients were included. Bland-Altman and Taffé methods demonstrated a proportional bias, in which low systolic BPs are overestimated, and high BPs are underestimated. Diastolic BPs were all overestimated, with increasing bias toward lower BPs. Sensitivity and specificity for detecting systolic and/or diastolic hypertension were 83 and 41%, respectively. ROC curves demonstrate an area under the curve (AUC) of 0.78 for systolic hypertension and of 0.93 for diastolic hypertension. BP variability was systematically higher in the ABPM measurements compared to the smartwatch measurements. Conclusion This study demonstrates that the BP measurements by the Samsung Galaxy Watch Active 2 show a systematic bias toward a calibration point, overestimating low BPs and underestimating high BPs, when investigated in both normotensive and hypertensive patients. Standards for traditional non-invasive sphygmomanometers are not met, but these standards are not fully applicable to cuffless devices, emphasizing the urgent need for new standards for cuffless devices. The smartwatch-based BP measurement is not yet ready for clinical usage. Future studies are needed to further validate wearable devices, and also to demonstrate new possibilities of non-invasive, high-frequency BP monitoring.
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Affiliation(s)
- Maarten Falter
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium
- Department of Cardiology, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Martijn Scherrenberg
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium
- Faculty of Medicine and Health Sciences, Antwerp University, Antwerp, Belgium
| | - Karen Driesen
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
| | - Zoë Pieters
- Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Toshiki Kaihara
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium
- Division of Cardiology, Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Linqi Xu
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium
- School of Nursing, Jilin University, Changchun, China
| | - Enrico Gianluca Caiani
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
- Institute of Electronics, Computer and Telecommunication Engineering, Consiglio Nazionale delle Ricerche, Milan, Italy
| | | | - Andrea Faini
- Department of Cardiovascular Neural and Metabolic Sciences, Istituto Auxologico Italiano, IRCCS, S. Luca Hospital, Milan, Italy
| | - Gianfranco Parati
- Department of Cardiovascular Neural and Metabolic Sciences, Istituto Auxologico Italiano, IRCCS, S. Luca Hospital, Milan, Italy
- Department of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
| | - Paul Dendale
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium
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17
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Heimark S, Eitzen I, Vianello I, Bøtker-Rasmussen KG, Mamen A, Hoel Rindal OM, Waldum-Grevbo B, Sandbakk Ø, Seeberg TM. Blood Pressure Response and Pulse Arrival Time During Exercise Testing in Well-Trained Individuals. Front Physiol 2022; 13:863855. [PMID: 35899026 PMCID: PMC9309297 DOI: 10.3389/fphys.2022.863855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 06/08/2022] [Indexed: 11/15/2022] Open
Abstract
Introduction: There is a lack of data describing the blood pressure response (BPR) in well-trained individuals. In addition, continuous bio-signal measurements are increasingly investigated to overcome the limitations of intermittent cuff-based BP measurements during exercise testing. Thus, the present study aimed to assess the BPR in well-trained individuals during a cycle ergometer test with a particular focus on the systolic BP (SBP) and to investigate pulse arrival time (PAT) as a continuous surrogate for SBP during exercise testing. Materials and Methods: Eighteen well-trained male cyclists were included (32.4 ± 9.4 years; maximal oxygen uptake 63 ± 10 ml/min/kg) and performed a stepwise lactate threshold test with 5-minute stages, followed by a continuous test to voluntary exhaustion with 1-min increments when cycling on an ergometer. BP was measured with a standard automated exercise BP cuff. PAT was measured continuously with a non-invasive physiological measurements device (IsenseU) and metabolic consumption was measured continuously during both tests. Results: At lactate threshold (281 ± 56 W) and maximal intensity test (403 ± 61 W), SBP increased from resting values of 136 ± 9 mmHg to maximal values of 219 ± 21 mmHg and 231 ± 18 mmHg, respectively. Linear within-participant regression lines between PAT and SBP showed a mean r2 of 0.81 ± 17. Conclusion: In the present study focusing on the BPR in well-trained individuals, we observed a more exaggerated systolic BPR than in comparable recent studies. Future research should follow up on these findings to clarify the clinical implications of the high BPR in well-trained individuals. In addition, PAT showed strong intra-individual associations, indicating potential use as a surrogate SBP measurement during exercise testing.
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Affiliation(s)
- Sondre Heimark
- Department of Nephrology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- *Correspondence: Sondre Heimark,
| | - Ingrid Eitzen
- Department of Smart Sensors and Microsystems, SINTEF Digital, Oslo, Norway
| | - Isabella Vianello
- Department of Smart Sensors and Microsystems, SINTEF Digital, Oslo, Norway
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | | | - Asgeir Mamen
- Kristiania University College, School of Health Sciences, Oslo, Norway
| | | | | | - Øyvind Sandbakk
- Centre for Elite Sports Research, Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Trine M. Seeberg
- Department of Smart Sensors and Microsystems, SINTEF Digital, Oslo, Norway
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Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability. J Hypertens 2022; 40:1449-1460. [PMID: 35708294 DOI: 10.1097/hjh.0000000000003224] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Many cuffless blood pressure (BP) measuring devices are currently on the market claiming that they provide accurate BP measurements. These technologies have considerable potential to improve the awareness, treatment, and management of hypertension. However, recent guidelines by the European Society of Hypertension do not recommend cuffless devices for the diagnosis and management of hypertension. OBJECTIVE This statement by the European Society of Hypertension Working Group on BP Monitoring and Cardiovascular Variability presents the types of cuffless BP technologies, issues in their validation, and recommendations for clinical practice. STATEMENTS Cuffless BP monitors constitute a wide and heterogeneous group of novel technologies and devices with different intended uses. Cuffless BP devices have specific accuracy issues, which render the established validation protocols for cuff BP devices inadequate for their validation. In 2014, the Institute of Electrical and Electronics Engineers published a standard for the validation of cuffless BP devices, and the International Organization for Standardization is currently developing another standard. The validation of cuffless devices should address issues related to the need of individual cuff calibration, the stability of measurements post calibration, the ability to track BP changes, and the implementation of machine learning technology. Clinical field investigations may also be considered and issues regarding the clinical implementation of cuffless BP readings should be investigated. CONCLUSION Cuffless BP devices have considerable potential for changing the diagnosis and management of hypertension. However, fundamental questions regarding their accuracy, performance, and implementation need to be carefully addressed before they can be recommended for clinical use.
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19
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A machine learning approach for hypertension detection based on photoplethysmography and clinical data. Comput Biol Med 2022; 145:105479. [DOI: 10.1016/j.compbiomed.2022.105479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/01/2022] [Accepted: 03/31/2022] [Indexed: 11/23/2022]
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20
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Athaya T, Choi S. A Review of Noninvasive Methodologies to Estimate the Blood Pressure Waveform. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22103953. [PMID: 35632360 PMCID: PMC9145242 DOI: 10.3390/s22103953] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/19/2022] [Accepted: 05/21/2022] [Indexed: 05/06/2023]
Abstract
Accurate estimation of blood pressure (BP) waveforms is critical for ensuring the safety and proper care of patients in intensive care units (ICUs) and for intraoperative hemodynamic monitoring. Normal cuff-based BP measurements can only provide systolic blood pressure (SBP) and diastolic blood pressure (DBP). Alternatively, the BP waveform can be used to estimate a variety of other physiological parameters and provides additional information about the patient's health. As a result, various techniques are being proposed for accurately estimating the BP waveforms. The purpose of this review is to summarize the current state of knowledge regarding the BP waveform, three methodologies (pressure-based, ultrasound-based, and deep-learning-based) used in noninvasive BP waveform estimation research and the feasibility of employing these strategies at home as well as in ICUs. Additionally, this article will discuss the physical concepts underlying both invasive and noninvasive BP waveform measurements. We will review historical BP waveform measurements, standard clinical procedures, and more recent innovations in noninvasive BP waveform monitoring. Although the technique has not been validated, it is expected that precise, noninvasive BP waveform estimation will be available in the near future due to its enormous potential.
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21
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Sola J, Cortes M, Perruchoud D, De Marco B, Lobo MD, Pellaton C, Wuerzner G, Fisher NDL, Shah J. Guidance for the Interpretation of Continual Cuffless Blood Pressure Data for the Diagnosis and Management of Hypertension. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 4:899143. [PMID: 35655524 PMCID: PMC9152366 DOI: 10.3389/fmedt.2022.899143] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Hypertension remains the leading risk factor for death worldwide. Despite its prevalence, success of blood pressure (BP) management efforts remains elusive, and part of the difficulty lies in the tool still used to diagnose, measure, and treat hypertension: the sphygmomanometer introduced by Samuel Siegfried Karl von Basch in 1867. In recent years, there has been an explosion of devices attempting to provide estimates of BP without a cuff, overcoming many limitations of cuff-based BP monitors. Unfortunately, the differences in underlying technologies between traditional BP cuffs and newer cuffless devices, as well as hesitancy of changing a well-implemented standard, still generate understandable skepticism about and reluctance to adopt cuffless BP monitors in clinical practice. This guidance document aims to navigate the scientific and medical communities through the types of cuffless devices and present examples of robust BP data collection which are better representations of a person's true BP. It highlights the differences between data collected by cuffless and traditional cuff-based devices and provides an initial framework of interpretation of the new cuffless datasets using, as an example, a CE-marked continual cuffless BP device (Aktiia BP Monitor, Aktiia, Switzerland). Demonstration of novel BP metrics, which have the potential to change the paradigm of hypertension diagnosis and treatment, are now possible for the first time with cuffless BP monitors that provide continual readings over long periods. Widespread adoption of continual cuffless BP monitors in healthcare will require a collaborative and thoughtful process, acknowledging that the transition from a legacy to a novel medical technology will be slow. Finally, this guidance concludes with a call to action to international scientific and expert associations to include cuffless BP monitors in original scientific research and in future versions of guidelines and standards.
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Affiliation(s)
| | | | | | | | - Melvin D. Lobo
- Barts NIHR Biomedical Research Centre, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - Cyril Pellaton
- Division of Cardiology, Réseau Hospitalier Neuchâtelois (RHNe), Neuchâtel, Switzerland
| | - Gregoire Wuerzner
- Service of Nephrology and Hypertension, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Naomi D. L. Fisher
- Division of Endocrinology, Diabetes and Hypertension, Brigham and Women‘s Hospital, Boston, MA, United States
| | - Jay Shah
- Aktiia SA, Neuchâtel, Switzerland
- Division of Cardiology, Mayo Clinic Arizona, Phoenix, AZ, United States
- *Correspondence: Jay Shah
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22
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Virtual management of hypertension: lessons from the COVID-19 pandemic-International Society of Hypertension position paper endorsed by World Hypertension League and European Society of Hypertension. J Hypertens 2022; 40:1435-1448. [PMID: 35579481 DOI: 10.1097/hjh.0000000000003205] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The coronavirus disease 2019 pandemic caused an unprecedented shift from in person care to delivering healthcare remotely. To limit infectious spread, patients and providers rapidly adopted distant evaluation with online or telephone-based diagnosis and management of hypertension. It is likely that virtual care of chronic diseases including hypertension will continue in some form into the future. The purpose of the International Society of Hypertension's (ISH) position paper is to provide practical guidance on the virtual management of hypertension to improve its diagnosis and blood pressure control based on the currently available evidence and international experts' opinion for nonpregnant adults. Virtual care represents the provision of healthcare services at a distance with communication conducted between healthcare providers, healthcare users and their circle of care. This statement provides consensus guidance on: selecting blood pressure monitoring devices, accurate home blood pressure assessments, delivering patient education virtually, health behavior modification, medication adjustment and long-term virtual monitoring. We further provide recommendations on modalities for the virtual assessment and management of hypertension across the spectrum of resource availability and patient ability.
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Avolio A, Cox J, Louka K, Shirbani F, Tan I, Qasem A, Butlin M. Challenges Presented by Cuffless Measurement of Blood Pressure if Adopted for Diagnosis and Treatment of Hypertension. Pulse (Basel) 2022; 10:34-45. [PMID: 36660438 PMCID: PMC9843645 DOI: 10.1159/000522660] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/09/2022] [Indexed: 01/22/2023] Open
Abstract
The global health burden presented by hypertension is providing increased motivation for improved means of collection of blood pressure (BP) data. A growing area of research and commercial activity is the use of wearable devices to provide BP data using non-invasive cuffless techniques. The accelerated progress in recent years, particularly relating to connectivity of smartphone technology, has promoted the availability of consumer devices that provide values of BP. The main types of devices are wrist-worn, watch-type devices with sensors that typically record a photoplethysmography (PPG) signal, sometimes also with an electrocardiography (ECG) signal. The general underlying concept of the cuffless BP measurement in most device types is the association of BP and the travel time of the arterial pulse between two locations, determined from the time delay between the ECG and PPG signals. Other methods may involve additional analysis of the PPG waveform features. Experimental data are presented to illustrate the challenges presented by cuffless BP techniques in obtaining reliable BP measurements when the change in BP is caused by different stimuli affecting cardiac and vascular mechanisms. These effects influence the association of the measured and physiological BP change, thus presenting significant challenges and potential limitations in the use of cuffless BP devices for the diagnosis and treatment of hypertension.
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24
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Abstract
Current hypertension guidelines recommend using the average values of several blood pressure (BP) readings obtained both in and out of the office for the diagnosis and management of hypertension. In-office BP measurement using an upper-arm cuff constitutes the evidence-based reference method for current BP classification and treatment targets. However, out-of-office BP evaluation using 24 h ambulatory or home BP monitoring is recommended by all major medical associations for obtaining further insights into the BP profile of an individual and how it relates to their daily activities. Importantly, the highly variable nature of office and out-of-office BP readings has been widely acknowledged, including the association of BP variability with cardiovascular outcomes. However, to date, the implications of BP variability on cardiovascular outcomes have largely been ignored, with limited application in clinical practice. Novel cuffless wearable technologies might provide a detailed assessment of the 24 h BP profile and behaviour over weeks or months. These devices offer many advantages for researchers and patients compared with traditional BP monitors, but their accuracy and utility remain uncertain. In this Review, we outline and compare conventional and novel methods and techniques for assessing average BP levels and BP variability, and reflect on the utility and potential of these methods for improving the treatment and management of patients with hypertension. The most commonly available blood pressure (BP) monitoring devices are useful for capturing a snapshot BP value, but most have limited utility in measuring BP variability. In this Review, Schutte and colleagues outline the advantages and disadvantages of conventional and novel techniques to measure average BP levels and BP variability. Although the dynamic nature of blood pressure (BP) is well-known, hypertension guidelines recommend using the average values of static BP readings (office or out-of-office), specifically aiming to level the fluctuations and peaks in BP readings. All current BP measurement methods have imperfect reproducibility owing to the continuous fluctuation in BP readings, making it difficult to accurately diagnose hypertension. Accumulating evidence from clinical trials, large registries and meta-analyses shows that increased BP variability predicts cardiovascular outcome, independently of the average BP values. To date, BP variability is overlooked, with limited application in clinical practice, probably owing to a variety of complex non-standardized BP variability assessment methods and indices, and uncertain thresholds and clinical usefulness. Novel cuffless wearable BP technologies can provide very large numbers of readings for days and months without the discomfort of traditional BP monitoring devices, and have the potential to replace current BP methods, once accuracy issues are resolved and their clinical usefulness is proved.
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25
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Abstract
Cuffless blood pressure (BP) measurement has become a popular field due to clinical need and technological opportunity. However, no method has been broadly accepted hitherto. The objective of this review is to accelerate progress in the development and application of cuffless BP measurement methods. We begin by describing the principles of conventional BP measurement, outstanding hypertension/hypotension problems that could be addressed with cuffless methods, and recent technological advances, including smartphone proliferation and wearable sensing, that are driving the field. We then present all major cuffless methods under investigation, including their current evidence. Our presentation includes calibrated methods (i.e., pulse transit time, pulse wave analysis, and facial video processing) and uncalibrated methods (i.e., cuffless oscillometry, ultrasound, and volume control). The calibrated methods can offer convenience advantages, whereas the uncalibrated methods do not require periodic cuff device usage or demographic inputs. We conclude by summarizing the field and highlighting potentially useful future research directions. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 24 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Ramakrishna Mukkamala
- Department of Bioengineering and Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA;
| | - George S Stergiou
- Hypertension Center STRIDE-7, School of Medicine, Third Department of Medicine, National and Kapodistrian University of Athens, Sotiria Hospital, Athens, Greece; ,
| | - Alberto P Avolio
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia;
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26
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Yi Z, Liu Z, Li W, Ruan T, Chen X, Liu J, Yang B, Zhang W. Piezoelectric Dynamics of Arterial Pulse for Wearable Continuous Blood Pressure Monitoring. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2110291. [PMID: 35285098 DOI: 10.1002/adma.202110291] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 02/09/2022] [Indexed: 06/14/2023]
Abstract
Piezoelectric arterial pulse wave dynamics are traditionally considered to be similar to those of typical blood pressure waves. However, achieving accurate continuous blood pressure wave monitoring based on arterial pulse waves remains challenging, because the correlation between piezoelectric pulse waves and their related blood pressure waves is unclear. To address this, the correlation between piezoelectric pulse waves and blood pressure waves is first elucidated via theoretical, simulation, and experimental analysis of these dynamics. Based on this correlation, the authors develop a wireless wearable continuous blood pressure monitoring system, with better portability than conventional systems that are based on the pulse wave velocity between multiple sensors. They explore the feasibility of achieving wearable continuous blood pressure monitoring without motion artifacts, using a single piezoelectric sensor. These findings eliminate the controversy over the arterial pulse wave piezoelectric response, and can potentially be used to develop a portable wearable continuous blood pressure monitoring device for the early prevention and daily control of hypertension.
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Affiliation(s)
- Zhiran Yi
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhaoxu Liu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Wenbo Li
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Tao Ruan
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xiang Chen
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jingquan Liu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Bin Yang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Wenming Zhang
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
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27
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Heimark S, Rindal OMH, Seeberg TM, Stepanov A, Boysen ES, Bøtker-Rasmussen KG, Mobæk NK, Søraas CL, Stenehjem AE, Fadl Elmula FEM, Waldum-Grevbo B. Blood pressure altering method affects correlation with pulse arrival time. Blood Press Monit 2022; 27:139-146. [PMID: 34855653 PMCID: PMC8893131 DOI: 10.1097/mbp.0000000000000577] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/07/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Pulse arrival time (PAT) is a potential main feature in cuff-less blood pressure (BP) monitoring. However, the precise relationship between BP parameters and PAT under varying conditions lacks a complete understanding. We hypothesize that simple test protocols fail to demonstrate the complex relationship between PAT and both SBP and DBP. Therefore, this study aimed to investigate the correlation between PAT and BP during two exercise modalities with differing BP responses using an unobtrusive wearable device. METHODS Seventy-five subjects, of which 43.7% had a prior diagnosis of hypertension, participated in an isometric and dynamic exercise test also including seated periods of rest prior to, in between and after. PAT was measured using a prototype wearable chest belt with a one-channel electrocardiogram and a photo-plethysmography sensor. Reference BP was measured auscultatory. RESULTS Mean individual correlation between PAT and SBP was -0.82 ± 0.14 in the full protocol, -0.79 ± 0.27 during isometric exercise and -0.77 ± 0.19 during dynamic exercise. Corresponding correlation between PAT and DBP was 0.25 ± 0.35, -0.74 ± 0.23 and 0.39 ± 0.41. CONCLUSION The results confirm PAT as a potential main feature to track changes in SBP. The relationship between DBP and PAT varied between exercise modalities, with the sign of the correlation changing from negative to positive between type of exercise modality. Thus, we hypothesize that simple test protocols fail to demonstrate the complex relationship between PAT and BP with emphasis on DBP.
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Affiliation(s)
- Sondre Heimark
- Department of Nephrology, Oslo University Hospital
- Section for Cardiovascular and Renal Research, Oslo University Hospital
- Institute of Clinical Medicine, University of Oslo
| | | | | | | | | | | | | | - Camilla L. Søraas
- Section for Cardiovascular and Renal Research, Oslo University Hospital
- Section for Environmental and Occupational Medicine, Oslo University Hospital
| | | | - Fadl Elmula M. Fadl Elmula
- Section for Cardiovascular and Renal Research, Oslo University Hospital
- Department of Acute Medicine, Oslo University Hospital, Oslo, Norway
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28
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Dese K, Ayana G, Lamesgin Simegn G. Low cost, non-invasive, and continuous vital signs monitoring device for pregnant women in low resource settings (Lvital device). HARDWAREX 2022; 11:e00276. [PMID: 35509911 PMCID: PMC9058728 DOI: 10.1016/j.ohx.2022.e00276] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/25/2022] [Accepted: 02/02/2022] [Indexed: 06/14/2023]
Abstract
Around 800 women die each day from complications of pregnancy and childbirth in the world. Vital Signs monitoring (such as blood pressure, pulse rate, and temperature) are among fundamental parameters of ensuring the health and safety of women and newborns during pregnancy, labor, and childbirth. Approximately, 10% of women experience hypertension (greater than140/90) during pregnancy. High blood pressure during pregnancy can cause extra stress on the heart and kidneys and can increase the risk of heart disease. Therefore, early recognition of abnormal vital signs, which are induced due to pregnancy can allow for timely identification of clinical deterioration. Currently used technologies are expensive and complex design with implementation challenges in low-resource settings where maternal morbidity and mortality is higher. Thus, considering the above need, here a hardware device has been designed and developed, which is a low cost, and portable for pregnant women's vital signs (with cuff-less blood pressure, heart rate, and body temperature) monitoring device. The developed device would have a remarkable benefit of monitoring the maternal vital signs especially for those in low resource settings, where there is a high paucity of vital signs monitoring devices.
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Affiliation(s)
- Kokeb Dese
- School of Biomedical Engineering, Jimma Institute of Technology, Jimma University-378, Jimma, Ethiopia
| | - Gelan Ayana
- School of Biomedical Engineering, Jimma Institute of Technology, Jimma University-378, Jimma, Ethiopia
- Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi- 39253, Korea
| | - Gizeaddis Lamesgin Simegn
- School of Biomedical Engineering, Jimma Institute of Technology, Jimma University-378, Jimma, Ethiopia
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29
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Marazzi NM, Guidoboni G, Zaid M, Sala L, Ahmad S, Despins L, Popescu M, Skubic M, Keller J. Combining Physiology-Based Modeling and Evolutionary Algorithms for Personalized, Noninvasive Cardiovascular Assessment Based on Electrocardiography and Ballistocardiography. Front Physiol 2022; 12:739035. [PMID: 35095545 PMCID: PMC8790319 DOI: 10.3389/fphys.2021.739035] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 10/14/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: This study proposes a novel approach to obtain personalized estimates of cardiovascular parameters by combining (i) electrocardiography and ballistocardiography for noninvasive cardiovascular monitoring, (ii) a physiology-based mathematical model for predicting personalized cardiovascular variables, and (iii) an evolutionary algorithm (EA) for searching optimal model parameters.Methods: Electrocardiogram (ECG), ballistocardiogram (BCG), and a total of six blood pressure measurements are recorded on three healthy subjects. The R peaks in the ECG are used to segment the BCG signal into single BCG curves for each heart beat. The time distance between R peaks is used as an input for a validated physiology-based mathematical model that predicts distributions of pressures and volumes in the cardiovascular system, along with the associated BCG curve. An EA is designed to search the generation of parameter values of the cardiovascular model that optimizes the match between model-predicted and experimentally-measured BCG curves. The physiological relevance of the optimal EA solution is evaluated a posteriori by comparing the model-predicted blood pressure with a cuff placed on the arm of the subjects to measure the blood pressure.Results: The proposed approach successfully captures amplitudes and timings of the most prominent peak and valley in the BCG curve, also known as the J peak and K valley. The values of cardiovascular parameters pertaining to ventricular function can be estimated by the EA in a consistent manner when the search is performed over five different BCG curves corresponding to five different heart-beats of the same subject. Notably, the blood pressure predicted by the physiology-based model with the personalized parameter values provided by the EA search exhibits a very good agreement with the cuff-based blood pressure measurement.Conclusion: The combination of EA with physiology-based modeling proved capable of providing personalized estimates of cardiovascular parameters and physiological variables of great interest, such as blood pressure. This novel approach opens the possibility for developing quantitative devices for noninvasive cardiovascular monitoring based on BCG sensing.
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Affiliation(s)
- Nicholas Mattia Marazzi
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States
| | - Giovanna Guidoboni
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States
- Department of Mathematics, University of Missouri, Columbia, MO, United States
- *Correspondence: Giovanna Guidoboni
| | - Mohamed Zaid
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States
| | - Lorenzo Sala
- Centre de Recherche Inria Saclay-Ile de France, Palaiseau, France
| | - Salman Ahmad
- Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, United States
| | - Laurel Despins
- Sinclair School of Nursing, University of Missouri, Columbia, MO, United States
| | - Mihail Popescu
- Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO, United States
| | - Marjorie Skubic
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States
| | - James Keller
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States
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30
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Benmira AM, Moranne O, Prelipcean C, Pambrun E, Dauzat M, Demattei C, Pérez-Martin A. Direct Determination rather than Oscillometric Estimation of Systolic Blood Pressure in Patients with Severe Chronic Kidney Disease. Am J Nephrol 2022; 53:41-49. [PMID: 35021175 DOI: 10.1159/000520996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 11/16/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Although arterial hypertension is a major concern in patients with chronic kidney disease (CKD), obtaining accurate systolic blood pressure (SBP) measurement is challenging in this population for whom automatic oscillometric devices may yield erroneous results. METHODS This cross-sectional study was conducted in 89 patients with stages 4, 5, and 5D CKD, for whom we compared SBP values obtained by the recently described systolic foot-to-apex time interval (SFATI) technique which provides direct SBP determination, the standard technique (Korotkoff sounds), and oscillometry. We investigated the effects of age, sex, diabetes, CKD stage, and pulse pressure to explain measurement errors defined as biases or misclassification relative to the SBP thresholds of 110-130-mm Hg. RESULTS All 3 techniques showed satisfactory reproducibility for SBP measurement (CCC > 0.84 and >0.91, respectively, in dialyzed and nondialyzed patients). The mean ± SD from SBP as determined via Korotkoff sounds was 1.7 ± 4.6 mm Hg for SFATI (CCC = 0.98) and 5.9 ± 9.3 mm Hg for oscillometry (CCC = 0.88). Referring to the 110-130-mm Hg SBP range outside which treatment prescription or adaptation is recommended for CKD patients, SFATI underestimated SBP in 3 patients and overestimated it in 1, whereas oscillometry underestimated SBP in 12 patients and overestimated it in 3. Higher pulse pressure was the main explanatory factor for measurement and classification errors. DISCUSSION/CONCLUSION SFATI provides accurate SBP measurements in patients with severe CKD and paves the way for the standardization of automated noninvasive blood pressure measurement devices. Before prescribing or adjusting antihypertensive therapy, physicians should be aware of the risk of misclassification when using oscillometry.
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Affiliation(s)
- Amir M Benmira
- Vascular Medicine, Nimes University Hospital, Nimes, France
- IDESP, INSERM & Montpellier University, Montpellier, France
| | - Olivier Moranne
- IDESP, INSERM & Montpellier University, Montpellier, France,
- Nephology - Dialysis - Apheresis, Nimes University Hospital, Nimes, France,
| | - Camelia Prelipcean
- Nephology - Dialysis - Apheresis, Nimes University Hospital, Nimes, France
| | - Emilie Pambrun
- Nephology - Dialysis - Apheresis, Nimes University Hospital, Nimes, France
| | - Michel Dauzat
- Vascular Medicine, Nimes University Hospital, Nimes, France
- EA2992, Montpellier University, Montpellier, France
| | | | - Antonia Pérez-Martin
- Vascular Medicine, Nimes University Hospital, Nimes, France
- IDESP, INSERM & Montpellier University, Montpellier, France
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31
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Martinez-Ríos E, Montesinos L, Alfaro-Ponce M, Pecchia L. A review of machine learning in hypertension detection and blood pressure estimation based on clinical and physiological data. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102813] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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32
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Quan X, Liu J, Roxlo T, Siddharth S, Leong W, Muir A, Cheong SM, Rao A. Advances in Non-Invasive Blood Pressure Monitoring. SENSORS (BASEL, SWITZERLAND) 2021; 21:s21134273. [PMID: 34206457 PMCID: PMC8271585 DOI: 10.3390/s21134273] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 06/18/2021] [Accepted: 06/18/2021] [Indexed: 01/30/2023]
Abstract
This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities.
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Affiliation(s)
- Xina Quan
- PyrAmes Inc., Cupertino, CA 95014, USA; (J.L.); (T.R.); (S.S.); (W.L.); (A.M.)
- Correspondence: ; Tel.: +1-408-216-0099
| | - Junjun Liu
- PyrAmes Inc., Cupertino, CA 95014, USA; (J.L.); (T.R.); (S.S.); (W.L.); (A.M.)
| | - Thomas Roxlo
- PyrAmes Inc., Cupertino, CA 95014, USA; (J.L.); (T.R.); (S.S.); (W.L.); (A.M.)
| | - Siddharth Siddharth
- PyrAmes Inc., Cupertino, CA 95014, USA; (J.L.); (T.R.); (S.S.); (W.L.); (A.M.)
| | - Weyland Leong
- PyrAmes Inc., Cupertino, CA 95014, USA; (J.L.); (T.R.); (S.S.); (W.L.); (A.M.)
| | - Arthur Muir
- PyrAmes Inc., Cupertino, CA 95014, USA; (J.L.); (T.R.); (S.S.); (W.L.); (A.M.)
| | - So-Min Cheong
- Department of Geography & Atmospheric Science, University of Kansas, Lawrence, KS 66045, USA;
| | - Anoop Rao
- Department of Pediatrics, Neonatology, Stanford University, Palo Alto, CA 94304, USA;
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33
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A novel art of continuous noninvasive blood pressure measurement. Nat Commun 2021; 12:1387. [PMID: 33654082 PMCID: PMC7925606 DOI: 10.1038/s41467-021-21271-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 12/17/2020] [Indexed: 01/31/2023] Open
Abstract
Wearable sensors to continuously measure blood pressure and derived cardiovascular variables have the potential to revolutionize patient monitoring. Current wearable methods analyzing time components (e.g., pulse transit time) still lack clinical accuracy, whereas existing technologies for direct blood pressure measurement are too bulky. Here we present an innovative art of continuous noninvasive hemodynamic monitoring (CNAP2GO). It directly measures blood pressure by using a volume control technique and could be used for small wearable sensors integrated in a finger-ring. As a software prototype, CNAP2GO showed excellent blood pressure measurement performance in comparison with invasive reference measurements in 46 patients having surgery. The resulting pulsatile blood pressure signal carries information to derive cardiac output and other hemodynamic variables. We show that CNAP2GO can self-calibrate and be miniaturized for wearable approaches. CNAP2GO potentially constitutes the breakthrough for wearable sensors for blood pressure and flow monitoring in both ambulatory and in-hospital clinical settings.
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34
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Taguchi S, Tamura K. Afternoon blood pressure increase on home blood pressure measurement: A forgotten entity? J Clin Hypertens (Greenwich) 2020; 22:2202-2203. [PMID: 33058448 DOI: 10.1111/jch.14078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 09/27/2020] [Accepted: 09/29/2020] [Indexed: 01/01/2023]
Affiliation(s)
- Shiniya Taguchi
- Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Kouichi Tamura
- Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan
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