A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography

Elise Jortberg,1 Ikaro Silva,1 Viprali Bhatkar,1 Ryan S McGinnis,2 Ellora Sen-Gupta,1 Briana Morey,1 John A Wright Jr,1 Jesus Pindado,1 Matt T Bianchi3 1MC10, Inc., Lexington, MA 02421, USA; 2Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT 05405, USA; 3Neur...

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Autores principales:	Jortberg E, Silva I, Bhatkar V, McGinnis RS, Sen-Gupta E, Morey B, Wright Jr JA, Pindado J, Bianchi MT
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2018
Materias:	electrocardiography electromyography respiration wearable Psychiatry RC435-571 Neurophysiology and neuropsychology QP351-495
Acceso en línea:	https://doaj.org/article/1ddc096eb0f34e6f96c002832f130b35
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spelling	oai:doaj.org-article:1ddc096eb0f34e6f96c002832f130b352021-12-02T04:03:16ZA novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography1179-1608https://doaj.org/article/1ddc096eb0f34e6f96c002832f130b352018-11-01T00:00:00Zhttps://www.dovepress.com/a-novel-adhesive-biosensor-system-for-detecting-respiration-cardiac-an-peer-reviewed-article-NSShttps://doaj.org/toc/1179-1608Elise Jortberg,1 Ikaro Silva,1 Viprali Bhatkar,1 Ryan S McGinnis,2 Ellora Sen-Gupta,1 Briana Morey,1 John A Wright Jr,1 Jesus Pindado,1 Matt T Bianchi3 1MC10, Inc., Lexington, MA 02421, USA; 2Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT 05405, USA; 3Neurology Department, Massachusetts General Hospital, Boston, MA 02114, USA Background: Although in-lab polysomnography (PSG) remains the gold standard for objective sleep monitoring, the use of at-home sensor systems has gained popularity in recent years. Two categories of monitoring, autonomic and limb movement physiology, are increasingly recognized as critical for sleep disorder phenotyping, yet at-home options remain limited outside of research protocols. The purpose of this study was to validate the BiostampRC® sensor system for respiration, electrocardiography (ECG), and leg electromyography (EMG) against gold standard PSG recordings.Methods: We report analysis of cardiac and respiratory data from 15 patients and anterior tibialis (AT) data from 19 patients undergoing clinical PSG for any indication who simultaneously wore BiostampRC® sensors on the chest and the bilateral AT muscles. BiostampRC® is a flexible, adhesive, wireless sensor capable of capturing accelerometry, ECG, and EMG. We compared BiostampRC® data and feature extractions with those obtained from PSG.Results: The heart rate extracted from BiostampRC® ECG showed strong agreement with the PSG (cohort root mean square error of 5 beats per minute). We found the thoracic BiostampRC® respiratory waveform, derived from its accelerometer, accurately calculated the respiratory rate (mean average error of 0.26 and root mean square error of 1.84 breaths per minute). The AT EMG signal supported periodic limb movement detection, with area under the curve of the receiver operating characteristic curve equaling 0.88. Upon completion, 88% of subjects indicated willingness to wear BiostampRC® at home on an exit survey.Conclusion: The results demonstrate that BiostampRC® is a tolerable and accurate method for capturing respiration, ECG, and AT EMG time series signals during overnight sleep when compared with simultaneous PSG recordings. The signal quality sufficiently supports analytics of clinical relevance. Larger longitudinal in-home studies are required to support the role of BiostampRC® in clinical management of sleep disorders involving the autonomic nervous system and limb movements. Keywords: electrocardiography, electromyography, respiration, wearableJortberg ESilva IBhatkar VMcGinnis RSSen-Gupta EMorey BWright Jr JAPindado JBianchi MTDove Medical PressarticleelectrocardiographyelectromyographyrespirationwearablePsychiatryRC435-571Neurophysiology and neuropsychologyQP351-495ENNature and Science of Sleep, Vol Volume 10, Pp 397-408 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	electrocardiography electromyography respiration wearable Psychiatry RC435-571 Neurophysiology and neuropsychology QP351-495
spellingShingle	electrocardiography electromyography respiration wearable Psychiatry RC435-571 Neurophysiology and neuropsychology QP351-495 Jortberg E Silva I Bhatkar V McGinnis RS Sen-Gupta E Morey B Wright Jr JA Pindado J Bianchi MT A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
description	Elise Jortberg,1 Ikaro Silva,1 Viprali Bhatkar,1 Ryan S McGinnis,2 Ellora Sen-Gupta,1 Briana Morey,1 John A Wright Jr,1 Jesus Pindado,1 Matt T Bianchi3 1MC10, Inc., Lexington, MA 02421, USA; 2Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT 05405, USA; 3Neurology Department, Massachusetts General Hospital, Boston, MA 02114, USA Background: Although in-lab polysomnography (PSG) remains the gold standard for objective sleep monitoring, the use of at-home sensor systems has gained popularity in recent years. Two categories of monitoring, autonomic and limb movement physiology, are increasingly recognized as critical for sleep disorder phenotyping, yet at-home options remain limited outside of research protocols. The purpose of this study was to validate the BiostampRC® sensor system for respiration, electrocardiography (ECG), and leg electromyography (EMG) against gold standard PSG recordings.Methods: We report analysis of cardiac and respiratory data from 15 patients and anterior tibialis (AT) data from 19 patients undergoing clinical PSG for any indication who simultaneously wore BiostampRC® sensors on the chest and the bilateral AT muscles. BiostampRC® is a flexible, adhesive, wireless sensor capable of capturing accelerometry, ECG, and EMG. We compared BiostampRC® data and feature extractions with those obtained from PSG.Results: The heart rate extracted from BiostampRC® ECG showed strong agreement with the PSG (cohort root mean square error of 5 beats per minute). We found the thoracic BiostampRC® respiratory waveform, derived from its accelerometer, accurately calculated the respiratory rate (mean average error of 0.26 and root mean square error of 1.84 breaths per minute). The AT EMG signal supported periodic limb movement detection, with area under the curve of the receiver operating characteristic curve equaling 0.88. Upon completion, 88% of subjects indicated willingness to wear BiostampRC® at home on an exit survey.Conclusion: The results demonstrate that BiostampRC® is a tolerable and accurate method for capturing respiration, ECG, and AT EMG time series signals during overnight sleep when compared with simultaneous PSG recordings. The signal quality sufficiently supports analytics of clinical relevance. Larger longitudinal in-home studies are required to support the role of BiostampRC® in clinical management of sleep disorders involving the autonomic nervous system and limb movements. Keywords: electrocardiography, electromyography, respiration, wearable
format	article
author	Jortberg E Silva I Bhatkar V McGinnis RS Sen-Gupta E Morey B Wright Jr JA Pindado J Bianchi MT
author_facet	Jortberg E Silva I Bhatkar V McGinnis RS Sen-Gupta E Morey B Wright Jr JA Pindado J Bianchi MT
author_sort	Jortberg E
title	A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
title_short	A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
title_full	A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
title_fullStr	A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
title_full_unstemmed	A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
title_sort	novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography
publisher	Dove Medical Press
publishDate	2018
url	https://doaj.org/article/1ddc096eb0f34e6f96c002832f130b35
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A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography

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