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Hussein O, Alkhader A, Gohar A, Bhat A. Home Sleep Apnea Testing for Obstructive Sleep Apnea. MISSOURI MEDICINE 2024; 121:60-65. [PMID: 38404435 PMCID: PMC10887466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Obstructive Sleep Apnea (OSA) is a major public health problem affecting almost one billion individuals worldwide. Ninety percent of patients with OSA are still undiagnosed. Although an attended polysomnography (PSG) testing is the gold standard to diagnose OSA, it is time-consuming and is associated with higher costs. The Home Sleep Apnea Testing (HSAT) is now available to diagnose OSA. Understanding the indications and limitations of HSAT is important to avoid misdiagnosis and improve patient outcomes.
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Affiliation(s)
- Omar Hussein
- Fellow Sleep Medicine, University of Missouri - Kansas City of School Medicine, Kansas City, Missouri
| | - Aseel Alkhader
- Research Assistant, University of Kansas Medical Center, Kansas City Kansas
| | - Ashraf Gohar
- Professor of Medicine, University of Missouri - Kansas City of School Medicine, Kansas City, Missouri
| | - Abid Bhat
- Professor of Medicine, University of Missouri - Kansas City of School Medicine, Kansas City, Missouri
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2
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Jayarathna T, Gargiulo GD, Lui GY, Breen PP. Electrodeless Heart and Respiratory Rate Estimation during Sleep Using a Single Fabric Band and Event-Based Edge Processing. SENSORS (BASEL, SWITZERLAND) 2022; 22:6689. [PMID: 36081149 PMCID: PMC9460329 DOI: 10.3390/s22176689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 08/26/2022] [Accepted: 09/01/2022] [Indexed: 06/15/2023]
Abstract
Heart rate (HR) and respiratory rate (RR) are two vital parameters of the body medically used for diagnosing short/long-term illness. Out-of-the-body, non-skin-contact HR/RR measurement remains a challenge due to imprecise readings. "Invisible" wearables integrated into day-to-day garments have the potential to produce precise readings with a comfortable user experience. Sleep studies and patient monitoring benefit from "Invisibles" due to longer wearability without significant discomfort. This paper suggests a novel method to reduce the footprint of sleep monitoring devices. We use a single silver-coated nylon fabric band integrated into a substrate of a standard cotton/nylon garment as a resistive elastomer sensor to measure air and blood volume change across the chest. We introduce a novel event-based architecture to process data at the edge device and describe two algorithms to calculate real-time HR/RR on ARM Cortex-M3 and Cortex-M4F microcontrollers. RR estimations show a sensitivity of 99.03% and a precision of 99.03% for identifying individual respiratory peaks. The two algorithms used for HR calculation show a mean absolute error of 0.81 ± 0.97 and 0.86±0.61 beats/min compared with a gold standard ECG-based HR. The event-based algorithm converts the respiratory/pulse waveform into instantaneous events, therefore reducing the data size by 40-140 times and requiring 33% less power to process and transfer data. Furthermore, we show that events hold enough information to reconstruct the original waveform, retaining pulse and respiratory activity. We suggest fabric sensors and event-based algorithms would drastically reduce the device footprint and increase the performance for HR/RR estimations during sleep studies, providing a better user experience.
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Affiliation(s)
- Titus Jayarathna
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Gaetano D. Gargiulo
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2750, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW 2052, Australia
- Translational Health Research Institute, Westmead, NSW 2145, Australia
| | - Gough Y. Lui
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Paul P. Breen
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW 2052, Australia
- Translational Health Research Institute, Westmead, NSW 2145, Australia
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3
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Estimation of Tidal Volume during Exercise Stress Test from Wearable-Device Measures of Heart Rate and Breathing Rate. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Tidal volume (TV), defined as the amount of air that moves in or out of the lungs with each respiratory cycle, is important in evaluating the respiratory function. Although TV can be reliably measured in laboratory settings, this information is hardly obtainable under everyday living conditions. Under such conditions, wearable devices could provide valuable support to monitor vital signs, such as heart rate (HR) and breathing rate (BR). The aim of this study was to develop a model to estimate TV from wearable-device measures of HR and BR during exercise. HR and BR were acquired through the Zephyr Bioharness 3.0 wearable device in nine subjects performing incremental cycling tests. For each subject, TV during exercise was obtained with a metabolic cart (Cosmed). A stepwise regression algorithm was used to create the model using as possible predictors HR, BR, age, and body mass index; the model was then validated using a leave-one-subject-out cross-validation procedure. The performance of the model was evaluated using the explained variance (R2), obtaining values ranging from 0.65 to 0.72. The proposed model is a valid method for TV estimation with wearable devices and can be considered not subject-specific and not instrumentation-specific.
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4
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Ganne C, Hampson JP, Toth E, Hupp NJ, Hampson JS, Mosher JC, Pati S, Lhatoo SD, Lacuey N. Limbic and paralimbic respiratory modulation: from inhibition to enhancement. Epilepsia 2022; 63:1799-1811. [PMID: 35352347 DOI: 10.1111/epi.17244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 03/25/2022] [Accepted: 03/28/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Increased understanding of the role of cortical structures in respiratory control may help the understanding of seizure-induced respiratory dysfunction that leads to sudden death in epilepsy (SUDEP). The aim of this study was to characterize respiratory responses to electrical stimulation (ES), including inhibition and enhancement of respiration. METHODS We prospectively recruited 19 consecutive patients with intractable epilepsy undergoing stereotactic EEG evaluation from June 2015 to June 2018. Inclusion criteria were patients ≥18 years and in whom ES was indicated for clinical mapping of ictal onset or eloquent cortex as part of the presurgical evaluation. ES was carried out at 50 Hz, 0.2 ms and 1-10 mA current intensity. Common brain regions sampled across all patients were- amygdala (AMY), hippocampus (HG), anterior cingulate gyrus (CING), orbitofrontal cortex (OrbF), temporal neocortex (TNC), temporal pole (TP) and entorhinal cortex (ERC). 755 stimulations were conducted. Quantitative analysis of breathing signal i.e., changes in breathing rate (BR), depth (TV), and minute ventilation (MV) was carried out during ES using the BreathMetrics breathing waveform analysis toolbox. Electrocardiogram, arterial oxygen saturation, end-tidal and transcutaneous carbon dioxide, nasal airflow, and abdominal and thoracic plethysmography were continuously monitored during stimulations. RESULTS Electrical stimulation of TP and CING (at lower current strengths <3mA) increased TV and MV. At 7-10mA, CING decreased TV and MV. On the other hand, decreased TV and MV occurred with stimulation of mesial temporal structures such as AMY and HG. Breathing changes were dependent on stimulation intensity. Lateral temporal, entorhinal, and orbitofrontal cortices did not affect breathing either way. SIGNIFICANCE These findings suggest that breathing responses other than apnea can be induced by ES. Identification of two regions, the temporal pole and anterior cingulate gyrus, for enhancement of breathing may be important in paving the way to future development of strategies for prevention of SUDEP.
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Affiliation(s)
- Chaitanya Ganne
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA
| | - Johnson P Hampson
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,The NINDS Center for SUDEP Research
| | - Emilia Toth
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA
| | - Norma J Hupp
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,The NINDS Center for SUDEP Research
| | - Jaison S Hampson
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA
| | - John C Mosher
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA
| | - Sandipan Pati
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA
| | - Samden D Lhatoo
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,The NINDS Center for SUDEP Research
| | - Nuria Lacuey
- Texas Institute of Restorative Neurotechnologies (TIRN), University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,Department of Neurology, University of Texas Health Science Center (UTHealth), Houston, Texas, USA.,The NINDS Center for SUDEP Research
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5
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Gren L, Dierschke K, Mattsson F, Assarsson E, Krais AM, Kåredal M, Lovén K, Löndahl J, Pagels J, Strandberg B, Tunér M, Xu Y, Wollmer P, Albin M, Nielsen J, Gudmundsson A, Wierzbicka A. Lung function and self-rated symptoms in healthy volunteers after exposure to hydrotreated vegetable oil (HVO) exhaust with and without particles. Part Fibre Toxicol 2022; 19:9. [PMID: 35073958 PMCID: PMC8785558 DOI: 10.1186/s12989-021-00446-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 12/23/2021] [Indexed: 11/22/2022] Open
Abstract
Background Diesel engine exhaust causes adverse health effects. Meanwhile, the impact of renewable diesel exhaust, such as hydrotreated vegetable oil (HVO), on human health is less known. Nineteen healthy volunteers were exposed to HVO exhaust for 3 h in a chamber with a double-blind, randomized setup. Exposure scenarios comprised of HVO exhaust from two modern non-road vehicles with 1) no aftertreatment system (‘HVOPM+NOx’ PM1: 93 µg m−3, EC: 54 µg m−3, NO: 3.4 ppm, NO2: 0.6 ppm), 2) an aftertreatment system containing a diesel oxidation catalyst and a diesel particulate filter (‘HVONOx’ PM1: ~ 1 µg m−3, NO: 2.0 ppm, NO2: 0.7 ppm) and 3) filtered air (FA) as control. The exposure concentrations were in line with current EU occupational exposure limits (OELs) of NO, NO2, formaldehyde, polycyclic aromatic hydrocarbons (PAHs), and the future OEL (2023) of elemental carbon (EC). The effect on nasal patency, pulmonary function, and self-rated symptoms were assessed. Calculated predicted lung deposition of HVO exhaust particles was compared to data from an earlier diesel exhaust study. Results The average total respiratory tract deposition of PM1 during HVOPM+NOx was 27 µg h−1. The estimated deposition fraction of HVO PM1 was 40–50% higher compared to diesel exhaust PM1 from an older vehicle (earlier study), due to smaller particle sizes of the HVOPM+NOx exhaust. Compared to FA, exposure to HVOPM+NOx and HVONOx caused higher incidence of self-reported symptoms (78%, 63%, respectively, vs. 28% for FA, p < 0.03). Especially, exposure to HVOPM+NOx showed 40–50% higher eye and throat irritation symptoms. Compared to FA, a decrement in nasal patency was found for the HVONOx exposures (− 18.1, 95% CI: − 27.3 to − 8.8 L min−1, p < 0.001), and for the HVOPM+NOx (− 7.4 (− 15.6 to 0.8) L min−1, p = 0.08). Overall, no clinically significant change was indicated in the pulmonary function tests (spirometry, peak expiratory flow, forced oscillation technique). Conclusion Short-term exposure to HVO exhaust concentrations corresponding to EU OELs for one workday did not cause adverse pulmonary function changes in healthy subjects. However, an increase in self-rated mild irritation symptoms, and mild decrease in nasal patency after both HVO exposures, may indicate irritative effects from exposure to HVO exhaust from modern non-road vehicles, with and without aftertreatment systems. Supplementary Information The online version contains supplementary material available at 10.1186/s12989-021-00446-7.
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Affiliation(s)
- Louise Gren
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden.,Lund University, NanoLund, 221 00, Lund, Sweden
| | - Katrin Dierschke
- Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden
| | - Fredrik Mattsson
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden
| | - Eva Assarsson
- Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden
| | - Annette M Krais
- Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden
| | - Monica Kåredal
- Lund University, NanoLund, 221 00, Lund, Sweden.,Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden
| | - Karin Lovén
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden.,Lund University, NanoLund, 221 00, Lund, Sweden
| | - Jakob Löndahl
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden.,Lund University, NanoLund, 221 00, Lund, Sweden
| | - Joakim Pagels
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden.,Lund University, NanoLund, 221 00, Lund, Sweden
| | - Bo Strandberg
- Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden
| | - Martin Tunér
- Division of Combustion Engines, Lund University, 221 00, Lund, Sweden
| | - Yiyi Xu
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Per Wollmer
- Department of Translational Medicine, Lund University, Lund, Sweden
| | - Maria Albin
- Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden.,Unit of Occupational Medicine, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Jörn Nielsen
- Division of Occupational and Environmental Medicine, Lund University, 223 63, Lund, Sweden
| | - Anders Gudmundsson
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden.,Lund University, NanoLund, 221 00, Lund, Sweden
| | - Aneta Wierzbicka
- Ergonomics and Aerosol Technology, Lund University, 221 00, Lund, Sweden. .,Centre for Healthy Indoor Environments, Lund University, 221 00, Lund, Sweden.
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Mannée DC, de Jongh F, van Helvoort H. Telemonitoring Techniques for Lung Volume Measurement: Accuracy, Artifacts and Effort. Front Digit Health 2021; 2:559483. [PMID: 34713036 PMCID: PMC8521879 DOI: 10.3389/fdgth.2020.559483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 08/12/2020] [Indexed: 11/13/2022] Open
Abstract
Telemonitoring becomes more important in pulmonary research. It can be used to decrease the pressure on the health care system, to lower the costs of health care and to increase quality of life of patients. Previous studies show contradictory results regarding the effectiveness of telemonitoring. According to multiple researchers, inefficiency can be a result of poor study design, low data quality and usability issues. To counteract these issues, this review proves for an in-depth explanation of four (potential) telemonitoring systems in terms of work principle, accuracy, disturbing factors and usability. The evaluated systems are portable spirometry/breath-by-breath analyzers, respiratory inductance and magnetic plethysmography and electrical impedance tomography. These insights can be used to select the optimal technique for a specific purpose in future studies.
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Affiliation(s)
| | - Frans de Jongh
- Pulmonary Department, Medisch Spectrum Twente, Enschede, Netherlands
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7
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Assessing the Tidal Volume through Wearables: A Scoping Review. SENSORS 2021; 21:s21124124. [PMID: 34208468 PMCID: PMC8233785 DOI: 10.3390/s21124124] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 05/28/2021] [Accepted: 06/11/2021] [Indexed: 01/10/2023]
Abstract
The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal volume during both daily activities and clinical settings. A screening of the literature (Pubmed, Scopus, and Web of Science) was carried out in December 2020 to collect studies: i. comparing one or more methodological approaches for the assessment of tidal volume with the outcome of a state-of-the-art measurement device (i.e., spirometry or optoelectronic plethysmography); ii. dealing with technological solutions designed to be exploited in wearable devices. From the initial 1031 documents, only 36 citations met the eligibility criteria. These studies highlighted that the tidal volume can be estimated by using different technologies ranging from IMUs to strain sensors (e.g., resistive, capacitive, inductive, electromagnetic, and optical) or acoustic sensors. Noticeably, the relative volumetric error of these solutions during quasi-static tasks (e.g., resting and sitting) is typically ≥10% but it deteriorates during dynamic motor tasks (e.g., walking). As such, additional efforts are required to improve the performance of these devices and to identify possible applications based on their accuracy and reliability.
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8
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Dou C, Huan H. Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices. SENSORS 2021; 21:s21103505. [PMID: 34069847 PMCID: PMC8157398 DOI: 10.3390/s21103505] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/10/2021] [Accepted: 05/13/2021] [Indexed: 11/30/2022]
Abstract
Respiration rate is an essential indicator of vital signs, which can demonstrate the physiological condition of the human body and provide clues to some diseases. Commercial Wi-Fi devices can provide a non-invasive, cost-effective and long-term respiration rate-monitoring scheme for home scenarios. However, previous studies show that the breathing depth and location may affect the detectability of respiratory signals. In this study, we leverage the variation of the Doppler spectral energy extracted from the channel state information (CSI) collected by Wi-Fi devices to track the chest displacement induced by respiration. First, the random phase is eliminated by phase-fitting method to obtain the complex CSI containing the Doppler shift. Then, the multipath decomposition of CSI is carried out to obtain the channel impulse response, which eliminates the interference phase of the time delay and retains the Doppler shift. The dynamic path units are also separate from the multipath, which overcomes the indoor multipath effect. Finally, we conduct a time–frequency analysis to dynamic units to accumulate Doppler spectral energy. Based on these ideas, we design a complete respiration rate-monitoring system to obtain the respiration rate by using the consistency between the Doppler energy change period and the respiratory cycle. We evaluate our system through extensive experiments in several typical home environments filled with multipath. Experimental results show that the errors of the three scenarios are approximate, the maximum error is less than 0.7 bpm, and the average errors are approximately 0.15 bpm. This result indicates that our scheme can achieve high precision respiration monitoring and has good anti-multipath ability compared with existing methods.
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9
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Wiegandt FC, Biegger D, Fast JF, Matusiak G, Mazela J, Ortmaier T, Doll T, Dietzel A, Bohnhorst B, Pohlmann G. Detection of Breathing Movements of Preterm Neonates by Recording Their Abdominal Movements with a Time-of-Flight Camera. Pharmaceutics 2021; 13:pharmaceutics13050721. [PMID: 34068978 PMCID: PMC8156597 DOI: 10.3390/pharmaceutics13050721] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/10/2021] [Accepted: 05/11/2021] [Indexed: 12/20/2022] Open
Abstract
In order to deliver an aerosolized drug in a breath-triggered manner, the initiation of the patient’s inspiration needs to be detected. The best-known systems monitoring breathing patterns are based on flow sensors. However, due to their large dead space volume, flow sensors are not advisable for monitoring the breathing of (preterm) neonates. Newly-developed respiratory sensors, especially when contact-based (invasive), can be tested on (preterm) neonates only with great effort due to clinical and ethical hurdles. Therefore, a physiological model is highly desirable to validate these sensors. For developing such a system, abdominal movement data of (preterm) neonates are required. We recorded time sequences of five preterm neonates’ abdominal movements with a time-of-flight camera and successfully extracted various breathing patterns and respiratory parameters. Several characteristic breathing patterns, such as forced breathing, sighing, apnea and crying, were identified from the movement data. Respiratory parameters, such as duration of inspiration and expiration, as well as respiratory rate and breathing movement over time, were also extracted. This work demonstrated that respiratory parameters of preterm neonates can be determined without contact. Therefore, such a system can be used for breathing detection to provide a trigger signal for breath-triggered drug release systems. Furthermore, based on the recorded data, a physiological abdominal movement model of preterm neonates can now be developed.
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Affiliation(s)
- Felix C. Wiegandt
- Division of Translational Biomedical Engineering, Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, 30625 Hannover, Germany; (D.B.); (T.D.)
- Correspondence: (F.C.W.); (G.P.); Tel.: +49-511-5350-287 (F.C.W.); +49-511-5350-116 (G.P.)
| | - David Biegger
- Division of Translational Biomedical Engineering, Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, 30625 Hannover, Germany; (D.B.); (T.D.)
| | - Jacob F. Fast
- Institute of Mechatronic Systems, Leibniz Universität Hannover, 30823 Garbsen, Germany; (J.F.F.); (T.O.)
- Department of Phoniatrics and Pediatric Audiology, Hannover Medical School, 30625 Hannover, Germany
| | - Grzegorz Matusiak
- Division of Infectious Diseases, Department of Neonatology, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (G.M.); (J.M.)
| | - Jan Mazela
- Division of Infectious Diseases, Department of Neonatology, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (G.M.); (J.M.)
| | - Tobias Ortmaier
- Institute of Mechatronic Systems, Leibniz Universität Hannover, 30823 Garbsen, Germany; (J.F.F.); (T.O.)
| | - Theodor Doll
- Division of Translational Biomedical Engineering, Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, 30625 Hannover, Germany; (D.B.); (T.D.)
- Department of Otorhinolaryngology, Hannover Medical School, 30625 Hannover, Germany
| | - Andreas Dietzel
- Institute of Microtechnology, Technische Universität Braunschweig, 38124 Braunschweig, Germany;
| | - Bettina Bohnhorst
- Department of Pediatric Pulmonology, Allergology and Neonatology, Hannover Medical School, 30625 Hannover, Germany;
| | - Gerhard Pohlmann
- Division of Translational Biomedical Engineering, Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, 30625 Hannover, Germany; (D.B.); (T.D.)
- Correspondence: (F.C.W.); (G.P.); Tel.: +49-511-5350-287 (F.C.W.); +49-511-5350-116 (G.P.)
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Nabavi S, Bhadra S. Oral Cavity Pressure Measurement-based Respiratory Monitoring System with Reduced Susceptibility to Motion Artifacts. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:5900-5904. [PMID: 33019317 DOI: 10.1109/embc44109.2020.9176425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In this paper, we propose a novel approach for respiratory monitoring through the direct measurement of oral cavity pressure. To measure the oral cavity pressure, a pressure sensor is placed inside the oral cavity. The intraorally obtained pressure signals are analyzed in the time-domain and validated against the conventional respiration monitoring belt (reference measurement). Tests have been performed on four subjects (four tests on each subject) in stationary and non-stationary conditions to evaluate the usage of the system in real life. Measurement from the proposed system shows that our approach can monitor the respiration rate with an accuracy of 99% when compared to the reference measurement. Moreover, the system can effectively track the respiration pattern and can detect breathing events independent of breathing routes, i.e., the nasal and oral. It has the minimum susceptibility to motion artifacts. Therefore, it has potential to be used as a wearable monitoring system for day to day life.
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11
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Continuous Vital Monitoring During Sleep and Light Activity Using Carbon-Black Elastomer Sensors. SENSORS 2020; 20:s20061583. [PMID: 32178307 PMCID: PMC7146453 DOI: 10.3390/s20061583] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/06/2020] [Accepted: 03/10/2020] [Indexed: 11/26/2022]
Abstract
The comfortable, continuous monitoring of vital parameters is still a challenge. The long-term measurement of respiration and cardiovascular signals is required to diagnose cardiovascular and respiratory diseases. Similarly, sleep quality assessment and the recovery period following acute treatments require long-term vital parameter datalogging. To address these requirements, we have developed “VitalCore”, a wearable continuous vital parameter monitoring device in the form of a T-shirt targeting the uninterrupted monitoring of respiration, pulse, and actigraphy. VitalCore uses polymer-based stretchable resistive bands as the primary sensor to capture breathing and pulse patterns from chest expansion. The carbon black-impregnated polymer is implemented in a U-shaped configuration and attached to the T-shirt with “interfacing” material along with the accompanying electronics. In this paper, VitalCore is bench tested and compared to gold standard respiration and pulse measurements to verify its functionality and further to assess the quality of data captured during sleep and during light exercise (walking). We show that these polymer-based sensors could identify respiratory peaks with a sensitivity of 99.44%, precision of 96.23%, and false-negative rate of 0.557% during sleep. We also show that this T-shirt configuration allows the wearer to sleep in all sleeping positions with a negligible difference of data quality. The device was also able to capture breathing during gait with 88.9–100% accuracy in respiratory peak detection.
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12
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Kebe M, Gadhafi R, Mohammad B, Sanduleanu M, Saleh H, Al-Qutayri M. Human Vital Signs Detection Methods and Potential Using Radars: A Review. SENSORS (BASEL, SWITZERLAND) 2020; 20:E1454. [PMID: 32155838 PMCID: PMC7085680 DOI: 10.3390/s20051454] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 02/25/2020] [Accepted: 03/02/2020] [Indexed: 02/04/2023]
Abstract
Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject's body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.
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Affiliation(s)
- Mamady Kebe
- System on Chip Center, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE; (M.K.); (R.G.); (M.S.); (H.S.); (M.A.-Q.)
| | - Rida Gadhafi
- System on Chip Center, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE; (M.K.); (R.G.); (M.S.); (H.S.); (M.A.-Q.)
- College of Engineering & IT (CEIT), University of Dubai, P.O. Box 14143, Dubai, UAE
| | - Baker Mohammad
- System on Chip Center, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE; (M.K.); (R.G.); (M.S.); (H.S.); (M.A.-Q.)
| | - Mihai Sanduleanu
- System on Chip Center, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE; (M.K.); (R.G.); (M.S.); (H.S.); (M.A.-Q.)
| | - Hani Saleh
- System on Chip Center, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE; (M.K.); (R.G.); (M.S.); (H.S.); (M.A.-Q.)
| | - Mahmoud Al-Qutayri
- System on Chip Center, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE; (M.K.); (R.G.); (M.S.); (H.S.); (M.A.-Q.)
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Belsare P, Senyurek VY, Imtiaz MH, Tiffany S, Sazonov E. Computation of Cigarette Smoke Exposure Metrics From Breathing. IEEE Trans Biomed Eng 2019; 67:2309-2316. [PMID: 31831405 DOI: 10.1109/tbme.2019.2958843] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Traditional metrics of smoke exposure in cigarette smokers are derived either from self-report, biomarkers, or puff topography. Methods involving biomarkers measure concentrations of nicotine, nicotine metabolites, or carbon monoxide. Puff-topography methods employ portable instruments to measure puff count, puff volume, puff duration, and inter-puff interval. In this article, we propose smoke exposure metrics calculated from the breathing signal and describe a novel algorithm for the computation of these metrics. The Personal Automatic Cigarette Tracker v2 (PACT-2) sensors, puff topography devices (CReSS), and video observation were used in a study of 38 moderate to heavy smokers in a controlled environment. Parameters of smoke inhalation including the start and end of each puff, inhale and exhale cycle, and smoke holding were computed from the breathing signal. From these, the traditional metrics of puff duration, inhale-exhale cycle duration, smoke holding duration, inter-puff interval, and novel Respiratory Smoke Exposure Metrics (RSEMs) such as inhale-exhale cycle volume, and inhale-exhale volume over time were calculated. The proposed RSEM algorithm to extract smoke exposure metrics named generated interclass correlations (ICCs) of 0.85 and 0.87 and Pearson's correlations of 0.97 and 0.77 with video observation and CReSS, respectively, for puff duration. Similarly, for the inhale-exhale duration, an ICC of 0.84 and Pearson's correlation of 0.81 was obtained with video observation. The RSEMs provided measures previously unavailable in research that are proportional to the depth and duration of smoke inhalation. The results suggest that the breathing signal may be used to compute smoke exposure metrics.
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Imtiaz MH, Ramos-Garcia RI, Wattal S, Tiffany S, Sazonov E. Wearable Sensors for Monitoring of Cigarette Smoking in Free-Living: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2019; 19:E4678. [PMID: 31661856 PMCID: PMC6864810 DOI: 10.3390/s19214678] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 10/23/2019] [Accepted: 10/24/2019] [Indexed: 01/28/2023]
Abstract
Globally, cigarette smoking is widespread among all ages, and smokers struggle to quit. The design of effective cessation interventions requires an accurate and objective assessment of smoking frequency and smoke exposure metrics. Recently, wearable devices have emerged as a means of assessing cigarette use. However, wearable technologies have inherent limitations, and their sensor responses are often influenced by wearers' behavior, motion and environmental factors. This paper presents a systematic review of current and forthcoming wearable technologies, with a focus on sensing elements, body placement, detection accuracy, underlying algorithms and applications. Full-texts of 86 scientific articles were reviewed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines to address three research questions oriented to cigarette smoking, in order to: (1) Investigate the behavioral and physiological manifestations of cigarette smoking targeted by wearable sensors for smoking detection; (2) explore sensor modalities employed for detecting these manifestations; (3) evaluate underlying signal processing and pattern recognition methodologies and key performance metrics. The review identified five specific smoking manifestations targeted by sensors. The results suggested that no system reached 100% accuracy in the detection or evaluation of smoking-related features. Also, the testing of these sensors was mostly limited to laboratory settings. For a realistic evaluation of accuracy metrics, wearable devices require thorough testing under free-living conditions.
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Affiliation(s)
- Masudul H Imtiaz
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.
| | - Raul I Ramos-Garcia
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.
| | - Shashank Wattal
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.
| | - Stephen Tiffany
- Department of Psychology, University at Buffalo, The State University of New York, Buffalo, NY 12246, USA.
| | - Edward Sazonov
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.
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Hanif U, Schneider LD, Trap L, Leary EB, Moore H, Guilleminault C, Jennum P, Sorensen HBD, Mignot EJM. Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology. Physiol Meas 2019; 40:025008. [DOI: 10.1088/1361-6579/ab0559] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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16
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Massaroni C, Venanzi C, Silvatti AP, Lo Presti D, Saccomandi P, Formica D, Giurazza F, Caponero MA, Schena E. Smart textile for respiratory monitoring and thoraco-abdominal motion pattern evaluation. JOURNAL OF BIOPHOTONICS 2018; 11:e201700263. [PMID: 29297202 DOI: 10.1002/jbio.201700263] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 01/01/2018] [Indexed: 05/21/2023]
Abstract
The use of wearable systems for monitoring vital parameters has gained wide popularity in several medical fields. The focus of the present study is the experimental assessment of a smart textile based on 12 fiber Bragg grating sensors for breathing monitoring and thoraco-abdominal motion pattern analysis. The feasibility of the smart textile for monitoring several temporal respiratory parameters (ie, breath-by-breath respiratory period, breathing frequency, duration of inspiratory and expiratory phases), volume variations of the whole chest wall and of its compartments is performed on 8 healthy male volunteers. Values gathered by the textile are compared to the data obtained by a motion analysis system, used as the reference instrument. Good agreement between the 2 systems on both respiratory period (bias of 0.01 seconds), breathing frequency (bias of -0.02 breaths/min) and tidal volume (bias of 0.09 L) values is demonstrated. Smart textile shows good performance in the monitoring of thoraco-abdominal pattern and its variation, as well.
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Affiliation(s)
- Carlo Massaroni
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Cecilia Venanzi
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Amanda P Silvatti
- Department of Physical Education, Universidade Federal de Viçosa Minas Gerais, Brazil
| | - Daniela Lo Presti
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | | | - Domenico Formica
- Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Francesco Giurazza
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Michele A Caponero
- Photonics Micro- and Nanostructures Laboratory, Research Centre of Frascati, Rome, Italy
| | - Emiliano Schena
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
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A Wearable System for Real-Time Continuous Monitoring of Physical Activity. JOURNAL OF HEALTHCARE ENGINEERING 2018; 2018:1878354. [PMID: 29849993 PMCID: PMC5925007 DOI: 10.1155/2018/1878354] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Accepted: 01/11/2018] [Indexed: 11/23/2022]
Abstract
Over the last decades, wearable systems have gained interest for monitoring of physiological variables, promoting health, and improving exercise adherence in different populations ranging from elite athletes to patients. In this paper, we present a wearable system for the continuous real-time monitoring of respiratory frequency (fR), heart rate (HR), and movement cadence during physical activity. The system has been experimentally tested in the laboratory (by simulating the breathing pattern with a mechanical ventilator) and by collecting data from one healthy volunteer. Results show the feasibility of the proposed device for real-time continuous monitoring of fR, HR, and movement cadence both in resting condition and during activity. Finally, different synchronization techniques have been investigated to enable simultaneous data collection from different wearable modules.
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Dumond R, Gastinger S, Rahman HA, Le Faucheur A, Quinton P, Kang H, Prioux J. Estimation of respiratory volume from thoracoabdominal breathing distances: comparison of two models of machine learning. Eur J Appl Physiol 2017; 117:1533-1555. [PMID: 28612121 DOI: 10.1007/s00421-017-3630-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 05/01/2017] [Indexed: 11/25/2022]
Abstract
PURPOSE The purposes of this study were to both improve the accuracy of respiratory volume (V) estimates using the respiratory magnetometer plethysmography (RMP) technique and facilitate the use of this technique. METHOD We compared two models of machine learning (ML) for estimating [Formula: see text]: a linear model (multiple linear regression-MLR) and a nonlinear model (artificial neural network-ANN), and we used cross-validation to validate these models. Fourteen healthy adults, aged [Formula: see text] years participated in the present study. The protocol was conducted in a laboratory test room. The anteroposterior displacements of the rib cage and abdomen, and the axial displacements of the chest wall and spine were measured using two pairs of magnetometers. [Formula: see text] was estimated from these four signals, and the respiratory volume was simultaneously measured using a spirometer ([Formula: see text]) under lying, sitting and standing conditions as well as various exercise conditions (working on computer, treadmill walking at 4 and 6 km[Formula: see text], treadmill running at 9 and 12 km [Formula: see text] and ergometer cycling at 90 and 110 W). RESULTS The results from the ANN model fitted the spirometer volume significantly better than those obtained through MLR. Considering all activities, the difference between [Formula: see text] and [Formula: see text] (bias) was higher for the MLR model ([Formula: see text] L) than for the ANN model ([Formula: see text] L). CONCLUSION Our results demonstrate that this new processing approach for RMP seems to be a valid tool for estimating V with sufficient accuracy during lying, sitting and standing and under various exercise conditions.
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Affiliation(s)
- Rémy Dumond
- Laboratoire Mouvement, Sport, Santé (EA 1274), Université de Rennes 2, Avenue Robert Schuman, 35170, Bruz, France.
- Département Sciences du sport et éducation physique, Ecole normale supérieure de Rennes, Campus de Ker Lann, Avenue Robert Schuman, 35170, Bruz, France.
| | - Steven Gastinger
- Laboratoire Mouvement, Sport, Santé (EA 1274), Université de Rennes 2, Avenue Robert Schuman, 35170, Bruz, France
- APCoSS, Institut de Formation en Éducation Physique et en Sport d'Angers (IFEPSA), Les Ponts de Cé, France
| | - Hala Abdul Rahman
- Laboratoire Mouvement, Sport, Santé (EA 1274), Université de Rennes 2, Avenue Robert Schuman, 35170, Bruz, France
- Laboratoire du Traitement du Signal et de l'Image, Université de Rennes 1, Campus de Beaulieu, Bâtiment 22, Rennes, 35042 Cedex, France
| | - Alexis Le Faucheur
- Laboratoire Mouvement, Sport, Santé (EA 1274), Université de Rennes 2, Avenue Robert Schuman, 35170, Bruz, France
- Département Sciences du sport et éducation physique, Ecole normale supérieure de Rennes, Campus de Ker Lann, Avenue Robert Schuman, 35170, Bruz, France
| | - Patrice Quinton
- Laboratoire Mouvement, Sport, Santé (EA 1274), Université de Rennes 2, Avenue Robert Schuman, 35170, Bruz, France
- Departement Informatique et télécommunications, Ecole normale supérieure de Rennes, Campus de Ker Lann, Avenue Robert Schuman, 35170, Bruz, France
| | - Haitao Kang
- Yuewu Electronic Technology Co., Ltd, Room 1008, Building B, No. 2305, Zuchongzhi Road, Shanghai, 201203, China
| | - Jacques Prioux
- Laboratoire Mouvement, Sport, Santé (EA 1274), Université de Rennes 2, Avenue Robert Schuman, 35170, Bruz, France.
- Département Sciences du sport et éducation physique, Ecole normale supérieure de Rennes, Campus de Ker Lann, Avenue Robert Schuman, 35170, Bruz, France.
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Validity of thoracic respiratory inductive plethysmography in high body mass index subjects. Respir Physiol Neurobiol 2017; 242:52-58. [PMID: 28363683 DOI: 10.1016/j.resp.2017.03.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Revised: 02/28/2017] [Accepted: 03/22/2017] [Indexed: 11/22/2022]
Abstract
We aim to evaluate thoracic respiratory inductive plethysmography (RIP) in high body mass index (BMI) subjects with a pneumotachometer (PT) as a reference. We simultaneously evaluated spontaneous breathing by RIP and PT in 10 low and 10 high BMI subjects at rest and in moderate exercise. We then recorded RIP amplitude with different excursions mimicking respiratory thoracic deformation, with different sizes of RIP belts surrounding cylinders of different perimeters with or without deformable foam simulating adipose tissue. RIP responses correlated with PT values in low and high BMI groups for inspiratory time (r=0.86 and r=0.91, respectively), expiratory time (r=0.96 and r=0.91, respectively) and amplitude (r=0.82 for both) but with a bias (-0.23±0.25L) for high BMI subjects. ANOVA revealed the effects of perimeter and simulated adiposity (p<0.001 for both). We concluded that thoracic perimeter and deformity of adipose tissue are responsible for biases in RIP response in high BMI subjects.
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Doherty C, Kubaski F, Tomatsu S, Shaffer TH. Non-invasive pulmonary function test on Morquio patients. JOURNAL OF RARE DISEASES RESEARCH & TREATMENT 2017; 2:55-62. [PMID: 30294725 PMCID: PMC6171363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Morquio patients, in many cases, present with severe tracheal narrowing and restrictive lung problems making them susceptible to high mortality arising from sleep apnea and related complications. Tracheal obstruction with growth imbalance, short neck, adeno and tonsillar hypertrophy, large mandible, and/or pectus carinatum also contributes to the challenges in managing the airway with intubation and extubation due to factors intrinsic to Morquio syndrome. Taken together, these issues lead to serious respiratory distress and life-threatening complications during anesthetic procedures. Furthermore, patients with Morquio syndrome frequently cannot perform standard pulmonary function tests as a result of their distinctive skeletal dysplasia and chest deformity, thus making diagnosis of incipient pulmonary disease difficult. In many cases, conventional spirometry is too difficult for patients to complete, deriving from issues with cooperation or clinical circumstance. Therefore, it is an unmet challenge to assess pulmonary insufficiency with standard pulmonary function test (PFT) with minimal effort. Non-invasive PFT such as respiratory inductance plethysmography, impulse oscillometry system, and pneumotachography were described in Morquio patients as compared with spirometry. Findings from our previous study indicate that these non-invasive tests are a reliable approach to evaluate lung function in a larger range of patients, and provide valuable clinical information otherwise unobtainable from invasive tests. In conclusion, the present study describes the utility of non-invasive (PFT) to accommodate a broad range of patients including intolerance to effort-dependent PFT.
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Affiliation(s)
| | - Francyne Kubaski
- Department of Biological Sciences, University of Delaware, Newark, DE, USA
- Nemours/Alfred I. duPont Hospital for Children, Wilmington, DE, USA
| | - Shunji Tomatsu
- Nemours/Alfred I. duPont Hospital for Children, Wilmington, DE, USA
- Department of Pediatrics, Gifu University, Gifu, Japan
- Department of Pediatrics, Thomas Jefferson University, Philadelphia, PA, USA
| | - Thomas H. Shaffer
- Nemours/Alfred I. duPont Hospital for Children, Wilmington, DE, USA
- Center for Pediatric Lung Research, Nemours/Alfred I. duPont Hospital for Children, Wilmington, DE, USA
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