An Inertial-Based Wearable System for Monitoring Vital Signs During Sleep

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2024 Jul 13

PMID 39000917

Authors

Spyridon Kontaxis

Foivos Kanellos

Adamantios Ntanis

Nicholas Kostikis

Spyridon Konitsiotis

George Rigas

Affiliations

Soon will be listed here.

Abstract

This study explores the feasibility of a wearable system to monitor vital signs during sleep. The system incorporates five inertial measurement units (IMUs) located on the waist, the arms, and the legs. To evaluate the performance of a novel framework, twenty-three participants underwent a sleep study, and vital signs, including respiratory rate (RR) and heart rate (HR), were monitored via polysomnography (PSG). The dataset comprises individuals with varying severity of sleep-disordered breathing (SDB). Using a single IMU sensor positioned at the waist, strong correlations of more than 0.95 with the PSG-derived vital signs were obtained. Low inter-participant mean absolute errors of about 0.66 breaths/min and 1.32 beats/min were achieved, for RR and HR, respectively. The percentage of data available for analysis, representing the time coverage, was 98.3% for RR estimation and 78.3% for HR estimation. Nevertheless, the fusion of data from IMUs positioned at the arms and legs enhanced the inter-participant time coverage of HR estimation by over 15%. These findings imply that the proposed methodology can be used for vital sign monitoring during sleep, paving the way for a comprehensive understanding of sleep quality in individuals with SDB.

References

Inan O, Migeotte P, Park K, Etemadi M, Tavakolian K, Casanella R . Ballistocardiography and seismocardiography: a review of recent advances. IEEE J Biomed Health Inform. 2014; 19(4):1414-27. DOI: 10.1109/JBHI.2014.2361732. View

Bailon R, Sornmo L, Laguna P . A robust method for ECG-based estimation of the respiratory frequency during stress testing. IEEE Trans Biomed Eng. 2006; 53(7):1273-85. DOI: 10.1109/TBME.2006.871888. View

Giovangrandi L, Inan O, Wiard R, Etemadi M, Kovacs G . Ballistocardiography--a method worth revisiting. Annu Int Conf IEEE Eng Med Biol Soc. 2012; 2011:4279-82. PMC: 4274997. DOI: 10.1109/IEMBS.2011.6091062. View

Liu G, Guo Y, Zhu Q, Huang B, Wang L . Estimation of respiration rate from three-dimensional acceleration data based on body sensor network. Telemed J E Health. 2011; 17(9):705-11. PMC: 3203837. DOI: 10.1089/tmj.2011.0022. View

Kostikis N, Rigas G, Konitsiotis S, Fotiadis D . Configurable Offline Sensor Placement Identification for a Medical Device Monitoring Parkinson's Disease. Sensors (Basel). 2021; 21(23). PMC: 8672276. DOI: 10.3390/s21237801. View

Lazaro J, Gil E, Bailon R, Minchole A, Laguna P . Deriving respiration from photoplethysmographic pulse width. Med Biol Eng Comput. 2012; 51(1-2):233-42. DOI: 10.1007/s11517-012-0954-0. View

Barfod C, Lauritzen M, Danker J, Soletormos G, Forberg J, Berlac P . Abnormal vital signs are strong predictors for intensive care unit admission and in-hospital mortality in adults triaged in the emergency department - a prospective cohort study. Scand J Trauma Resusc Emerg Med. 2012; 20:28. PMC: 3384463. DOI: 10.1186/1757-7241-20-28. View

Mokhlespour Esfahani M, Nussbaum M . Preferred Placement and Usability of a Smart Textile System vs. Inertial Measurement Units for Activity Monitoring. Sensors (Basel). 2018; 18(8). PMC: 6111998. DOI: 10.3390/s18082501. View

Brekke I, Puntervoll L, Pedersen P, Kellett J, Brabrand M . The value of vital sign trends in predicting and monitoring clinical deterioration: A systematic review. PLoS One. 2019; 14(1):e0210875. PMC: 6333367. DOI: 10.1371/journal.pone.0210875. View

10.

Cesareo A, Biffi E, Cuesta-Frau D, DAngelo M, Aliverti A . A novel acquisition platform for long-term breathing frequency monitoring based on inertial measurement units. Med Biol Eng Comput. 2020; 58(4):785-804. DOI: 10.1007/s11517-020-02125-9. View

11.

Petit C, Bezemer R, Atallah L . A review of recent advances in data analytics for post-operative patient deterioration detection. J Clin Monit Comput. 2017; 32(3):391-402. DOI: 10.1007/s10877-017-0054-7. View

12.

Kontaxis S, Lazaro J, Corino V, Sandberg F, Bailon R, Laguna P . ECG-Derived Respiratory Rate in Atrial Fibrillation. IEEE Trans Biomed Eng. 2019; 67(3):905-914. DOI: 10.1109/TBME.2019.2923587. View

13.

Bricout A, Fontecave-Jallon J, Pepin J, Gumery P . Accelerometry-derived respiratory index estimating apnea-hypopnea index for sleep apnea screening. Comput Methods Programs Biomed. 2021; 207:106209. DOI: 10.1016/j.cmpb.2021.106209. View

14.

Hughes S, Liu H, Zheng D . Influences of Sensor Placement Site and Subject Posture on Measurement of Respiratory Frequency Using Triaxial Accelerometers. Front Physiol. 2020; 11:823. PMC: 7363979. DOI: 10.3389/fphys.2020.00823. View

15.

Liu H, Allen J, Zheng D, Chen F . Recent development of respiratory rate measurement technologies. Physiol Meas. 2019; 40(7):07TR01. DOI: 10.1088/1361-6579/ab299e. View

16.

Zschocke J, Kluge M, Pelikan L, Graf A, Glos M, Muller A . Detection and analysis of pulse waves during sleep via wrist-worn actigraphy. PLoS One. 2020; 14(12):e0226843. PMC: 6938353. DOI: 10.1371/journal.pone.0226843. View

17.

Schipper F, Van Sloun R, Grassi A, Derkx R, Overeem S, Fonseca P . Estimation of respiratory rate and effort from a chest-worn accelerometer using constrained and recursive principal component analysis. Physiol Meas. 2021; 42(4). DOI: 10.1088/1361-6579/abf01f. View

18.

Jafari Tadi M, Lehtonen E, Saraste A, Tuominen J, Koskinen J, Teras M . Gyrocardiography: A New Non-invasive Monitoring Method for the Assessment of Cardiac Mechanics and the Estimation of Hemodynamic Variables. Sci Rep. 2017; 7(1):6823. PMC: 5533710. DOI: 10.1038/s41598-017-07248-y. View

19.

Varon C, Morales J, Lazaro J, Orini M, Deviaene M, Kontaxis S . A Comparative Study of ECG-derived Respiration in Ambulatory Monitoring using the Single-lead ECG. Sci Rep. 2020; 10(1):5704. PMC: 7109157. DOI: 10.1038/s41598-020-62624-5. View

20.

Massaroni C, Nicolo A, Presti D, Sacchetti M, Silvestri S, Schena E . Contact-Based Methods for Measuring Respiratory Rate. Sensors (Basel). 2019; 19(4). PMC: 6413190. DOI: 10.3390/s19040908. View