1
|
Lapitan DG, Rogatkin DA, Molchanova EA, Tarasov AP. Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering. Sci Rep 2024; 14:6546. [PMID: 38503856 PMCID: PMC10951216 DOI: 10.1038/s41598-024-57297-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/16/2024] [Indexed: 03/21/2024] Open
Abstract
Pre-processing of the photoplethysmography (PPG) signal plays an important role in the analysis of the pulse wave signal. The task of pre-processing is to remove noise from the PPG signal, as well as to transmit the signal without any distortions for further analysis. The integrity of the pulse waveform is essential since many cardiovascular parameters are calculated from it using morphological analysis. Digital filters with infinite impulse response (IIR) are widely used in the processing of PPG signals. However, such filters tend to change the pulse waveform. The aim of this work is to quantify the PPG signal distortions that occur during IIR filtering in order to select a most suitable filter and its parameters. To do this, we collected raw finger PPG signals from 20 healthy volunteers and processed them by 5 main digital IIR filters (Butterworth, Bessel, Elliptic, Chebyshev type I and type II) with varying parameters. The upper cutoff frequency varied from 2 to 10 Hz and the filter order-from 2nd to 6th. To assess distortions of the pulse waveform, we used the following indices: skewness signal quality index (SSQI), reflection index (RI) and ejection time compensated (ETc). It was found that a decrease in the upper cutoff frequency leads to damping of the dicrotic notch and a phase shift of the pulse wave signal. The minimal distortions of a PPG signal are observed when using Butterworth, Bessel and Elliptic filters of the 2nd order. Therefore, we can recommend these filters for use in applications aimed at morphological analysis of finger PPG waveforms of healthy subjects.
Collapse
Affiliation(s)
- Denis G Lapitan
- Moscow Regional Research and Clinical Institute ("MONIKI"), 129110, Moscow, Russia.
| | - Dmitry A Rogatkin
- Moscow Regional Research and Clinical Institute ("MONIKI"), 129110, Moscow, Russia
| | | | - Andrey P Tarasov
- Moscow Regional Research and Clinical Institute ("MONIKI"), 129110, Moscow, Russia
- National Research Centre "Kurchatov Institute", 123182, Moscow, Russia
| |
Collapse
|
2
|
Casado CA, Lopez MB. Face2PPG: An Unsupervised Pipeline for Blood Volume Pulse Extraction From Faces. IEEE J Biomed Health Inform 2023; 27:5530-5541. [PMID: 37610907 DOI: 10.1109/jbhi.2023.3307942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
Photoplethysmography (PPG) signals have become a key technology in many fields, such as medicine, well-being, or sports. Our work proposes a set of pipelines to extract remote PPG signals (rPPG) from the face robustly, reliably, and configurably. We identify and evaluate the possible choices in the critical steps of unsupervised rPPG methodologies. We assess a state-of-the-art processing pipeline in six different datasets, incorporating important corrections in the methodology that ensure reproducible and fair comparisons. In addition, we extend the pipeline by proposing three novel ideas; 1) a new method to stabilize the detected face based on a rigid mesh normalization; 2) a new method to dynamically select the different regions in the face that provide the best raw signals, and 3) a new RGB to rPPG transformation method, called Orthogonal Matrix Image Transformation (OMIT) based on QR decomposition, that increases robustness against compression artifacts. We show that all three changes introduce noticeable improvements in retrieving rPPG signals from faces, obtaining state-of-the-art results compared with unsupervised, non-learning-based methodologies and, in some databases, very close to supervised, learning-based methods. We perform a comparative study to quantify the contribution of each proposed idea. In addition, we depict a series of observations that could help in future implementations.
Collapse
|
3
|
Liao S, Liu H, Lin WH, Zheng D, Chen F. Filtering-induced changes of pulse transmit time across different ages: a neglected concern in photoplethysmography-based cuffless blood pressure measurement. Front Physiol 2023; 14:1172150. [PMID: 37560157 PMCID: PMC10407099 DOI: 10.3389/fphys.2023.1172150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 07/12/2023] [Indexed: 08/11/2023] Open
Abstract
Background: Pulse transit time (PTT) is a key parameter in cuffless blood pressure measurement based on photoplethysmography (PPG) signals. In wearable PPG sensors, raw PPG signals are filtered, which can change the timing of PPG waveform feature points, leading to inaccurate PTT estimation. There is a lack of comprehensive investigation of filtering-induced PTT changes in subjects with different ages. Objective: This study aimed to quantitatively investigate the effects of aging and PTT definition on the infinite impulse response (IIR) filtering-induced PTT changes. Methods: One hundred healthy subjects in five different ranges of age (i.e., 20-29, 30-39, 40-49, 50-59, and over 60 years old, 20 subjects in each) were recruited. Electrocardiogram (ECG) and PPG signals were recorded simultaneously for 120 s. PTT was calculated from the R wave of ECG and PPG waveform features. Eight PTT definitions were developed from different PPG waveform feature points. The raw PPG signals were preprocessed then further low-pass filtered. The difference between PTTs derived from preprocessed and filtered PPG signals, and the relative difference, were calculated and compared among five age groups and eight PTT definitions using the analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. Linear regression analysis was used to investigate the relationship between age and filtering-induced PTT changes. Results: Filtering-induced PTT difference and the relative difference were significantly influenced by age and PTT definition (p < 0.001 for both). Aging effect on filtering-induced PTT changes was consecutive with a monotonous trend under all PTT definitions. The age groups with maximum and minimum filtering-induced PTT changes depended on the definition. In all subjects, the PTT defined by maximum peak of PPG had the minimum filtering-induced PTT changes (mean: 16.16 ms and 5.65% for PTT difference and relative difference). The changes of PTT defined by maximum first PPG derivative had the strongest linear relationship with age (R-squared: 0.47 and 0.46 for PTT difference relative difference). Conclusion: The filtering-induced PTT changes are significantly influenced by age and PTT definition. These factors deserve further consideration to improve the accuracy of PPG-based cuffless blood pressure measurement using wearable sensors.
Collapse
Affiliation(s)
- Shangdi Liao
- Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Haipeng Liu
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
| | - Wan-Hua Lin
- Chinese Academy of Sciences Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, China
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
| | - Fei Chen
- Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
| |
Collapse
|
4
|
Pineda-Alpizar F, Arriola-Valverde S, Vado-Chacón M, Sossa-Rojas D, Liu H, Zheng D. Real-Time Evaluation of Time-Domain Pulse Rate Variability Parameters in Different Postures and Breathing Patterns Using Wireless Photoplethysmography Sensor: Towards Remote Healthcare in Low-Resource Communities. Sensors (Basel) 2023; 23:s23094246. [PMID: 37177450 PMCID: PMC10181559 DOI: 10.3390/s23094246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/20/2023] [Accepted: 04/23/2023] [Indexed: 05/15/2023]
Abstract
Photoplethysmography (PPG) signals have been widely used in evaluating cardiovascular biomarkers, however, there is a lack of in-depth understanding of the remote usage of this technology and its viability for underdeveloped countries. This study aims to quantitatively evaluate the performance of a low-cost wireless PPG device in detecting ultra-short-term time-domain pulse rate variability (PRV) parameters in different postures and breathing patterns. A total of 30 healthy subjects were recruited. ECG and PPG signals were simultaneously recorded in 3 min using miniaturized wearable sensors. Four heart rate variability (HRV) and PRV parameters were extracted from ECG and PPG signals, respectively, and compared using analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. In addition, the data loss was calculated as the percentage of missing sampling points. Posture did not present statistical differences across the PRV parameters but a statistical difference between indicators was found. Strong variation was found for the RMSSD indicator in the standing posture. The sitting position in both breathing patterns demonstrated the lowest data loss (1.0 ± 0.6 and 1.0 ± 0.7) and the lowest percentage of different factors for all indicators. The usage of commercial PPG and BLE devices can allow the reliable extraction of the PPG signal and PRV indicators in real time.
Collapse
Affiliation(s)
- Felipe Pineda-Alpizar
- Industrial Design Engineering Department, Costa Rica Institute of Technology, Cartago 7050, Costa Rica
| | - Sergio Arriola-Valverde
- Electronics Engineering Department, Costa Rica Institute of Technology, Cartago 7050, Costa Rica
| | - Mitzy Vado-Chacón
- Respiratory Therapy Department, Santa Paula University, San Jose 2633, Costa Rica
| | - Diego Sossa-Rojas
- Respiratory Therapy Department, Santa Paula University, San Jose 2633, Costa Rica
| | - Haipeng Liu
- Center of Intelligent Healthcare, Coventry University, Coventry CV1 5FB, UK
| | - Dingchang Zheng
- Center of Intelligent Healthcare, Coventry University, Coventry CV1 5FB, UK
| |
Collapse
|
5
|
Valenti S, Volpes G, Parisi A, Peri D, Lee J, Faes L, Busacca A, Pernice R. Wearable Multisensor Ring-Shaped Probe for Assessing Stress and Blood Oxygenation: Design and Preliminary Measurements. Biosensors (Basel) 2023; 13:bios13040460. [PMID: 37185535 PMCID: PMC10136507 DOI: 10.3390/bios13040460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 03/31/2023] [Accepted: 04/03/2023] [Indexed: 05/17/2023]
Abstract
The increasing interest in innovative solutions for health and physiological monitoring has recently fostered the development of smaller biomedical devices. These devices are capable of recording an increasingly large number of biosignals simultaneously, while maximizing the user's comfort. In this study, we have designed and realized a novel wearable multisensor ring-shaped probe that enables synchronous, real-time acquisition of photoplethysmographic (PPG) and galvanic skin response (GSR) signals. The device integrates both the PPG and GSR sensors onto a single probe that can be easily placed on the finger, thereby minimizing the device footprint and overall size. The system enables the extraction of various physiological indices, including heart rate (HR) and its variability, oxygen saturation (SpO2), and GSR levels, as well as their dynamic changes over time, to facilitate the detection of different physiological states, e.g., rest and stress. After a preliminary SpO2 calibration procedure, measurements have been carried out in laboratory on healthy subjects to demonstrate the feasibility of using our system to detect rapid changes in HR, skin conductance, and SpO2 across various physiological conditions (i.e., rest, sudden stress-like situation and breath holding). The early findings encourage the use of the device in daily-life conditions for real-time monitoring of different physiological states.
Collapse
Affiliation(s)
- Simone Valenti
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| | - Gabriele Volpes
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| | - Antonino Parisi
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| | - Daniele Peri
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| | - Jinseok Lee
- Department of Biomedical Engineering, Kyung Hee University, Yongin 17104, Republic of Korea
| | - Luca Faes
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| | - Alessandro Busacca
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| | - Riccardo Pernice
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy
| |
Collapse
|
6
|
Poliński A. Continuous blood pressure monitoring by photoplethysmography - signal preprocessing requirements based on blood flow modelling. Physiol Meas 2023; 44. [PMID: 36827709 DOI: 10.1088/1361-6579/acbf00] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 02/24/2023] [Indexed: 02/26/2023]
Abstract
Objective.The aim of the study is to investigate the effect of the signal sampling frequency and low-pass filtering on the accuracy of the localisation of the fiducial points of the photoplethysmographic signal (PPG), and thus on the estimation of the blood pressure (i.e. the accuracy of the estimation).Approach.Statistical analysis was performed on 3,799 data samples taken from a publicly available database. Four PPG fiducial points of each sample signal were examined in the study.Main results.Simulation suggests that for noise-free data, cubic spline interpolation causes the sampling frequency (in the considered range of 62.5-500 Hz) to have only limited influence on localisation of the fiducial point. Better results were obtained for the pulse transit time (PTT) than pulse arrival time (PAT) approach. The acceptable filter band depends on the selected fiducial point and PAT or PTT approach. The best results were obtained for the tangent fiducial point.Significance.The presented results make it possible to estimate the minimum requirements for the sampling frequency and filtering of the PPG signal in order to obtain a reliable estimation of blood pressure.
Collapse
Affiliation(s)
- Artur Poliński
- Department of Biomedical Engineering, Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, Gabriela Narutowicza 11/12, Gdańsk, Poland
| |
Collapse
|
7
|
Mejía-Mejía E, Kyriacou PA. Effects of noise and filtering strategies on the extraction of pulse rate variability from photoplethysmograms. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
|
8
|
Kralj L, Lenasi H. Wavelet analysis of laser Doppler microcirculatory signals: Current applications and limitations. Front Physiol 2023; 13:1076445. [PMID: 36741808 PMCID: PMC9895103 DOI: 10.3389/fphys.2022.1076445] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/28/2022] [Indexed: 01/21/2023] Open
Abstract
Laser Doppler flowmetry (LDF) has long been considered a gold standard for non-invasive assessment of skin microvascular function. Due to the laser Doppler (LD) microcirculatory signal's complex biological and physiological context, using spectral analysis is advisable to extract as many of the signal's properties as feasible. Spectral analysis can be performed using either a classical Fourier transform (FT) technique, which has the disadvantage of not being able to localize a signal in time, or wavelet analysis (WA), which provides both the time and frequency localization of the inspected signal. So far, WA of LD microcirculatory signals has revealed five characteristic frequency intervals, ranging from 0.005 to 2 Hz, each of which being related to a specific physiological influence modulating skin microcirculatory response, providing for a more thorough analysis of the signals measured in healthy and diseased individuals. Even though WA is a valuable tool for analyzing and evaluating LDF-measured microcirculatory signals, limitations remain, resulting in a lack of analytical standardization. As a more accurate assessment of human skin microcirculation may better enhance the prognosis of diseases marked by microvascular dysfunction, searching for improvements to the WA method is crucial from the clinical point of view. Accordingly, we have summarized and discussed WA application and its limitations when evaluating LD microcirculatory signals, and presented insight into possible future improvements. We adopted a novel strategy when presenting the findings of recent studies using WA by focusing on frequency intervals to contrast the findings of the various studies undertaken thus far and highlight their disparities.
Collapse
Affiliation(s)
- Lana Kralj
- Institute of Physiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Helena Lenasi
- Institute of Physiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia,*Correspondence: Helena Lenasi,
| |
Collapse
|
9
|
Stockwell SJ, Kwok TC, Morgan SP, Sharkey D, Hayes-Gill BR. Forehead monitoring of heart rate in neonatal intensive care. Front Physiol 2023; 14:1127419. [PMID: 37082236 PMCID: PMC10110846 DOI: 10.3389/fphys.2023.1127419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/21/2023] [Indexed: 04/22/2023] Open
Abstract
Heart rate is an extremely important physiological parameter to measure in critically unwell infants, as it is the main physiological marker that changes in response to a change in infant condition. Heart rate is routinely measured peripherally on a limb with a pulse oximeter. However, when infants are critically unwell, the blood supply to these peripheries is reduced in preference for central perfusion of vital organs such as the brain and heart. Measurement of heart rate with a reflection mode photoplethysmogram (PPG) sensor on the forehead could help minimise this problem and make it easier for other important medical equipment, such as cannulas, to be placed on the limbs. This study compares heart rates measured with a forehead-based PPG sensor against a wrist-based PPG sensor in 19 critically unwell infants in neonatal intensive care collecting 198 h of data. The two heart rates were compared using positive percentage agreement, Spearman's correlation coefficient and Bland-Altman analysis. The forehead PPG sensor showed good agreement with the wrist-based PPG sensor with limits of agreement of 8.44 bpm, bias of -0.22 bpm; positive percentage agreement of 98.87%; and Spearman's correlation coefficient of 0.9816. The analysis demonstrates that the forehead is a reliable alternative location for measuring vital signs using the PPG.
Collapse
Affiliation(s)
- S. J. Stockwell
- Optics and Photonics Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
| | - T. C. Kwok
- Centre for Perinatal Research, Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - S. P. Morgan
- Optics and Photonics Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
| | - D. Sharkey
- Centre for Perinatal Research, Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - B. R. Hayes-Gill
- Optics and Photonics Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
- *Correspondence: B. R. Hayes-Gill,
| |
Collapse
|
10
|
Li B, Jiang W, Peng J, Li X. Deep learning-based remote-photoplethysmography measurement from short-time facial video. Physiol Meas 2022; 43. [PMID: 36215976 DOI: 10.1088/1361-6579/ac98f1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 10/10/2022] [Indexed: 02/07/2023]
Abstract
Objective. Efficient non-contact heart rate (HR) measurement from facial video has received much attention in health monitoring. Past methods relied on prior knowledge and an unproven hypothesis to extract remote photoplethysmography (rPPG) signals, e.g. manually designed regions of interest (ROIs) and the skin reflection model.Approach. This paper presents a short-time end to end HR estimation framework based on facial features and temporal relationships of video frames. In the proposed method, a deep 3D multi-scale network with cross-layer residual structure is designed to construct an autoencoder and extract robust rPPG features. Then, a spatial-temporal fusion mechanism is proposed to help the network focus on features related to rPPG signals. Both shallow and fused 3D spatial-temporal features are distilled to suppress redundant information in the complex environment. Finally, a data augmentation strategy is presented to solve the problem of uneven distribution of HR in existing datasets.Main results. The experimental results on four face-rPPG datasets show that our method overperforms the state-of-the-art methods and requires fewer video frames. Compared with the previous best results, the proposed method improves the root mean square error (RMSE) by 5.9%, 3.4% and 21.4% on the OBF dataset (intra-test), COHFACE dataset (intra-test) and UBFC dataset (cross-test), respectively.Significance. Our method achieves good results on diverse datasets (i.e. highly compressed video, low-resolution and illumination variation), demonstrating that our method can extract stable rPPG signals in short time.
Collapse
Affiliation(s)
- Bin Li
- School of Information Science and Technology, Northwest University, Xi'an, People's Republic of China
| | - Wei Jiang
- School of Information Science and Technology, Northwest University, Xi'an, People's Republic of China
| | - Jinye Peng
- School of Information Science and Technology, Northwest University, Xi'an, People's Republic of China
| | - Xiaobai Li
- Center for Machine Vision and Signal Analysis, University of Oulu, Oulu
| |
Collapse
|
11
|
Mohammed N, Cluff K, Sutton M, Villafana-Ibarra B, Loflin BE, Griffith JL, Becker R, Bhandari S, Alruwaili F, Desai J. A Flexible Near-Field Biosensor for Multisite Arterial Blood Flow Detection. Sensors (Basel) 2022; 22:8389. [PMID: 36366092 PMCID: PMC9657423 DOI: 10.3390/s22218389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 10/24/2022] [Accepted: 10/29/2022] [Indexed: 06/16/2023]
Abstract
Modern wearable devices show promising results in terms of detecting vital bodily signs from the wrist. However, there remains a considerable need for a device that can conform to the human body's variable geometry to accurately detect those vital signs and to understand health better. Flexible radio frequency (RF) resonators are well poised to address this need by providing conformable bio-interfaces suitable for different anatomical locations. In this work, we develop a compact wearable RF biosensor that detects multisite hemodynamic events due to pulsatile blood flow through noninvasive tissue-electromagnetic (EM) field interaction. The sensor consists of a skin patch spiral resonator and a wearable transceiver. During resonance, the resonator establishes a strong capacitive coupling with layered dielectric tissues due to impedance matching. Therefore, any variation in the dielectric properties within the near-field of the coupled system will result in field perturbation. This perturbation also results in RF carrier modulation, transduced via a demodulator in the transceiver unit. The main elements of the transceiver consist of a direct digital synthesizer for RF carrier generation and a demodulator unit comprised of a resistive bridge coupled with an envelope detector, a filter, and an amplifier. In this work, we build and study the sensor at the radial artery, thorax, carotid artery, and supraorbital locations of a healthy human subject, which hold clinical significance in evaluating cardiovascular health. The carrier frequency is tuned at the resonance of the spiral resonator, which is 34.5 ± 1.5 MHz. The resulting transient waveforms from the demodulator indicate the presence of hemodynamic events, i.e., systolic upstroke, systolic peak, dicrotic notch, and diastolic downstroke. The preliminary results also confirm the sensor's ability to detect multisite blood flow events noninvasively on a single wearable platform.
Collapse
Affiliation(s)
- Noor Mohammed
- Department of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA 01003, USA
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
| | - Kim Cluff
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
| | - Mark Sutton
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
| | | | - Benjamin E. Loflin
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
- Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Jacob L. Griffith
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Ryan Becker
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Subash Bhandari
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
| | - Fayez Alruwaili
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
- Department of Biomedical Engineering, Rowan University, Glassboro, NJ 08028, USA
| | - Jaydip Desai
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA
| |
Collapse
|
12
|
Sarkar M, Assaad M. Noninvasive Non-Contact SpO 2 Monitoring Using an Integrated Polarization-Sensing CMOS Imaging Sensor. Sensors (Basel) 2022; 22:7796. [PMID: 36298147 PMCID: PMC9608125 DOI: 10.3390/s22207796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND In the diagnosis and primary health care of an individual, estimation of the pulse rate and blood oxygen saturation (SpO2) is critical. The pulse rate and SpO2 are determined by methods including photoplethysmography (iPPG), light spectroscopy, and pulse oximetry. These devices need to be compact, non-contact, and noninvasive for real-time health monitoring. Reflection-based iPPG is becoming popular as it allows non-contact estimation of the heart rate and SpO2. Most iPPG methods capture temporal data and form complex computations, and thus real-time measurements and spatial visualization are difficult. METHOD In this research work, reflective mode polarized imaging-based iPPG is proposed. For polarization imaging, a custom image sensor with wire grid polarizers on each pixel is designed. Each pixel has a wire grid of varying transmission axes, allowing phase detection of the incoming light. The phase information of the backscattered light from the fingertips of 12 healthy volunteers was recorded in both the resting as well as the excited states. These data were then processed using MATLAB 2021b software. RESULTS The phase information provides quantitative information on the reflection from the superficial and deep layers of skin. The ratio of deep to superficial layer backscattered phase information is shown to be directly correlated and linearly increasing with an increase in the SpO2 and heart rate. CONCLUSIONS The phase-based measurements help to monitor the changes in the resting and excited state heart rate and SpO2 in real time. Furthermore, the use of the ratio of phase information helps to make the measurements independent of the individual skin traits and thus increases the accuracy of the measurements. The proposed iPPG works in ambient light, relaxing the instrumentation requirement and helping the system to be compact and portable.
Collapse
Affiliation(s)
- Mukul Sarkar
- Electrical Engineering Department, IIT Delhi, Hauz Khas, New Delhi 110016, India
| | - Maher Assaad
- Department of Electrical and Computer Engineering, Ajman University, Ajman P.O. Box 346, United Arab Emirates
| |
Collapse
|
13
|
Khalid SG, Ali SM, Liu H, Qurashi AG, Ali U. Photoplethysmography temporal marker-based machine learning classifier for anesthesia drug detection. Med Biol Eng Comput 2022. [PMID: 36063352 PMCID: PMC9537122 DOI: 10.1007/s11517-022-02658-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 08/22/2022] [Indexed: 11/15/2022]
Abstract
Anesthesia drug overdose hazards and lack of gold standards in anesthesia monitoring lead to an urgent need for accurate anesthesia drug detection. To investigate the PPG waveform features affected by anesthesia drugs and develop a machine-learning classifier with high anesthesia drug sensitivity. This study used 64 anesthesia and non-anesthesia patient data (32 cases each), extracted from Queensland and MIMIC-II databases, respectively. The key waveform features (total area, rising time, width 75%, 50%, and 25%) were extracted from 16,310 signal recordings (5-s duration). Discriminant analysis, support vector machine (SVM), and K-nearest neighbor (KNN) were evaluated by splitting the dataset into halve training (11 patients, 8570 segments) and halve testing dataset (11 patients, 7740 segments). Significant differences exist between PPG waveform features of anesthesia and non-anesthesia groups (p < 0.05) except total area feature (p > 0.05). The KNN classifier achieved 91.7% (AUC = 0.95) anesthesia detection accuracy with the highest sensitivity (0.88) and specificity (0.90) as compared to other classifiers. Kohen’s kappa also shows almost perfect agreement (0.79) with the KNN classifier. The KNN classifier trained with significant PPG features has the potential to be used as a reliable, non-invasive, and low-cost method for the detection of anesthesia drugs for depth analysis during surgical operations and postoperative monitoring.
Collapse
|
14
|
Ismail SNA, Nayan NA, Jaafar R, May Z. Recent Advances in Non-Invasive Blood Pressure Monitoring and Prediction Using a Machine Learning Approach. Sensors (Basel) 2022; 22:6195. [PMID: 36015956 PMCID: PMC9412312 DOI: 10.3390/s22166195] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/25/2022] [Accepted: 08/04/2022] [Indexed: 06/15/2023]
Abstract
Blood pressure (BP) monitoring can be performed either invasively via arterial catheterization or non-invasively through a cuff sphygmomanometer. However, for conscious individuals, traditional cuff-based BP monitoring devices are often uncomfortable, intermittent, and impractical for frequent measurements. Continuous and non-invasive BP (NIBP) monitoring is currently gaining attention in the human health monitoring area due to its promising potentials in assessing the health status of an individual, enabled by machine learning (ML), for various purposes such as early prediction of disease and intervention treatment. This review presents the development of a non-invasive BP measuring tool called sphygmomanometer in brief, summarizes state-of-the-art NIBP sensors, and identifies extended works on continuous NIBP monitoring using commercial devices. Moreover, the NIBP predictive techniques including pulse arrival time, pulse transit time, pulse wave velocity, and ML are elaborated on the basis of bio-signals acquisition from these sensors. Additionally, the different BP values (systolic BP, diastolic BP, mean arterial pressure) of the various ML models adopted in several reported studies are compared in terms of the international validation standards developed by the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) for clinically-approved BP monitors. Finally, several challenges and possible solutions for the implementation and realization of continuous NIBP technology are addressed.
Collapse
Affiliation(s)
- Siti Nor Ashikin Ismail
- Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia
| | - Nazrul Anuar Nayan
- Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia
- Institute Islam Hadhari, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia
| | - Rosmina Jaafar
- Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia
| | - Zazilah May
- Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia
- Electrical and Electronic Engineering Department, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia
| |
Collapse
|
15
|
Charlton PH, Pilt K, Kyriacou PA. Establishing best practices in photoplethysmography signal acquisition and processing. Physiol Meas 2022; 43. [PMID: 35508148 PMCID: PMC9136485 DOI: 10.1088/1361-6579/ac6cc4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 05/04/2022] [Indexed: 11/19/2022]
Abstract
Photoplethysmography is now widely utilised by clinical devices such as pulse oximeters, and wearable devices such as smartwatches. It holds great promise for health monitoring in daily life. This editorial considers whether it would be possible and beneficial to establish best practices for photoplethysmography signal acquisition and processing. It reports progress made towards this, balanced with the challenges of working with a diverse range of photoplethysmography device designs and intended applications, each of which could benefit from different approaches to signal acquisition and processing. It concludes that there are several potential benefits to establishing best practices. However, it is not yet clear whether it is possible to establish best practices which hold across the range of photoplethysmography device designs and applications.
Collapse
Affiliation(s)
- Peter H Charlton
- Department of Public Health and Primary Care, Cambridge University, Strangeways Research Laboratory, 2 Worts' Causeway, Cambridge, CB1 8RN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Kristjan Pilt
- Department of Health Technologies, Tallinn University of Technology, Ehitajate tee 5, Tallinn, Harjumaa, 19086, ESTONIA
| | - Panayiotis A Kyriacou
- School of Mathematics Computer Science and Engineering, City University of London, Northampton Square, London, EC1V 0HB, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| |
Collapse
|
16
|
Koch MJ, Duy PQ, Grannan BL, Patel AB, Raymond SB, Agarwalla PK, Kahle KT, Butler WE. Angiographic Pulse Wave Coherence in the Human Brain. Front Bioeng Biotechnol 2022; 10:873530. [PMID: 35592552 PMCID: PMC9110661 DOI: 10.3389/fbioe.2022.873530] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
A stroke volume of arterial blood that arrives to the brain housed in the rigid cranium must be matched over the cardiac cycle by an equivalent volume of ejected venous blood. We hypothesize that the brain maintains this equilibrium by organizing coherent arterial and venous pulse waves. To test this hypothesis, we applied wavelet computational methods to diagnostic cerebral angiograms in four human patients, permitting the capture and analysis of cardiac frequency phenomena from fluoroscopic images acquired at faster than cardiac rate. We found that the cardiac frequency reciprocal phase of a small region of interest (ROI) in a named artery predicts venous anatomy pixel-wise and that the predicted pixels reconstitute venous bolus passage timing. Likewise, a small ROI in a named vein predicts arterial anatomy and arterial bolus passage timing. The predicted arterial and venous pixel groups maintain phase complementarity across the bolus travel. We thus establish a novel computational method to analyze vascular pulse waves from minimally invasive cerebral angiograms and provide the first direct evidence of arteriovenous coupling in the intact human brain. This phenomenon of arteriovenous coupling may be a physiologic mechanism for how the brain precisely maintains mechanical equilibrium against volume displacement and kinetic energy transfer resulting from cyclical deformations with each heartbeat. The study also paves the way to study deranged arteriovenous coupling as an underappreciated pathophysiologic disturbance in a myriad of neurological pathologies linked by mechanical disequilibrium.
Collapse
Affiliation(s)
- Matthew J. Koch
- Department of Neurosurgery, University of Florida, Gainesville, FL, United States
| | - Phan Q. Duy
- Medical Scientist Training Program, Yale University School of Medicine, New Haven, CT, United States
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, United States
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, United States
| | - Benjamin L. Grannan
- Department of Neurosurgery, University of Washington Medicine, Seattle, WA, United States
| | - Aman B. Patel
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
| | - Scott B. Raymond
- Department of Radiology, University of Vermont, Burlington, VT, United States
| | - Pankaj K. Agarwalla
- Department of Neurosurgery, Rutgers New Jersey Medical School, Newark, NJ, United States
| | - Kristopher T. Kahle
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, United States
- Broad Institute of MIT and Harvard, Cambridge, MA, United States
- MGH Hydrocephalus and Neurodevelopmental Disorders Program, Massachusetts General Hospital, Boston, MA, United States
| | - William E. Butler
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
| |
Collapse
|
17
|
Solé Morillo Á, Lambert Cause J, Baciu VE, da Silva B, Garcia-Naranjo JC, Stiens J. PPG EduKit: An Adjustable Photoplethysmography Evaluation System for Educational Activities. Sensors 2022; 22:s22041389. [PMID: 35214290 PMCID: PMC8963096 DOI: 10.3390/s22041389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/20/2022] [Accepted: 02/01/2022] [Indexed: 02/01/2023]
Abstract
The grown interest in healthcare applications has made biomedical engineering one of the fastest growing disciplines in recent years. Photoplethysmography (PPG) has gained popularity in recent years due to its versatility for noninvasive monitoring of vital signs such as heart rate, respiratory rate, blood oxygen saturation and blood pressure. In this work, an adjustable PPG-based educational device called PPG EduKit, which aims to facilitate the learning of the PPG technology for a wide range of engineering and medical disciplines is proposed. Through the use of this educational platform, the PPG signal can be understood, modified and implemented along with the extraction of its relevant physiological information from a didactic, intuitive and practical way. The PPG Edukit is evaluated for the extraction of physiological parameters such as heart rate and blood oxygen level, demonstrating how its features contribute to engineering and medical students to assimilate technical concepts in electrical circuits, biomedical instrumentation, and human physiology.
Collapse
Affiliation(s)
- Ángel Solé Morillo
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium; (V.-E.B.); (J.S.)
- Correspondence: (A.S.M.); (J.L.C.); (B.d.S.)
| | - Joan Lambert Cause
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium; (V.-E.B.); (J.S.)
- Department of Biomedical Engineering, Universidad de Oriente, Santiago de Cuba 90500, Cuba
- Correspondence: (A.S.M.); (J.L.C.); (B.d.S.)
| | - Vlad-Eusebiu Baciu
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium; (V.-E.B.); (J.S.)
| | - Bruno da Silva
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium; (V.-E.B.); (J.S.)
- Correspondence: (A.S.M.); (J.L.C.); (B.d.S.)
| | - Juan C. Garcia-Naranjo
- Biophysics and Medical Physics Center, Universidad de Oriente, Santiago de Cuba 90500, Cuba;
| | - Johan Stiens
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium; (V.-E.B.); (J.S.)
| |
Collapse
|
18
|
Allen J, Zheng D, Kyriacou PA, Elgendi M. Photoplethysmography (PPG): state-of-the-art methods and applications. Physiol Meas 2021; 42. [PMID: 34842179 DOI: 10.1088/1361-6579/ac2d82] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 10/06/2021] [Indexed: 11/12/2022]
Affiliation(s)
- John Allen
- Research Centre for Intelligent Healthcare, Coventry University, Coventry United Kingdom.,Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne United Kingdom
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry United Kingdom.,Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne United Kingdom
| | - Panicos A Kyriacou
- Research Centre for Biomedical Engineering, City, University of London, London United Kingdom
| | - Mohamed Elgendi
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, 8008, Zurich, Switzerland
| |
Collapse
|
19
|
Khanam FTZ, Perera AG, Al-Naji A, Gibson K, Chahl J. Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks. J Imaging 2021; 7:122. [PMID: 34460758 PMCID: PMC8404938 DOI: 10.3390/jimaging7080122] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/18/2021] [Accepted: 07/19/2021] [Indexed: 12/28/2022] Open
Abstract
Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland-Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.
Collapse
Affiliation(s)
- Fatema-Tuz-Zohra Khanam
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
| | - Asanka G. Perera
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
| | - Ali Al-Naji
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
- Electrical Engineering Technical College, Middle Technical University, Baghdad 10022, Iraq
| | - Kim Gibson
- Clinical and Health Sciences, City East Campus, University of South Australia, North Terrace, Adelaide, SA 5000, Australia;
| | - Javaan Chahl
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
| |
Collapse
|