Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study
BackgroundPopulation aging is posing multiple social and economic challenges to society. One such challenge is the social and economic burden related to increased health care expenditure caused by early institutionalizations. The use of modern pervasive computing technology makes it possible to cont...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2021-06-01
|
| Series: | JMIR mHealth and uHealth |
| Online Access: | https://mhealth.jmir.org/2021/6/e24666 |
| _version_ | 1819243388152578048 |
|---|---|
| author | Schütz, Narayan Saner, Hugo Botros, Angela Pais, Bruno Santschi, Valérie Buluschek, Philipp Gatica-Perez, Daniel Urwyler, Prabitha Müri, René M Nef, Tobias |
| author_facet | Schütz, Narayan Saner, Hugo Botros, Angela Pais, Bruno Santschi, Valérie Buluschek, Philipp Gatica-Perez, Daniel Urwyler, Prabitha Müri, René M Nef, Tobias |
| author_sort | Schütz, Narayan |
| collection | DOAJ |
| description | BackgroundPopulation aging is posing multiple social and economic challenges to society. One such challenge is the social and economic burden related to increased health care expenditure caused by early institutionalizations. The use of modern pervasive computing technology makes it possible to continuously monitor the health status of community-dwelling older adults at home. Early detection of health issues through these technologies may allow for reduced treatment costs and initiation of targeted preventive measures leading to better health outcomes. Sleep is a key factor when it comes to overall health and many health issues manifest themselves with associated sleep deteriorations. Sleep quality and sleep disorders such as sleep apnea syndrome have been extensively studied using various wearable devices at home or in the setting of sleep laboratories. However, little research has been conducted evaluating the potential of contactless and continuous sleep monitoring in detecting early signs of health problems in community-dwelling older adults.
ObjectiveIn this work we aim to evaluate which contactlessly measurable sleep parameter is best suited to monitor perceived and actual health status changes in older adults.
MethodsWe analyzed real-world longitudinal (up to 1 year) data from 37 community-dwelling older adults including more than 6000 nights of measured sleep. Sleep parameters were recorded by a pressure sensor placed beneath the mattress, and corresponding health status information was acquired through weekly questionnaires and reports by health care personnel. A total of 20 sleep parameters were analyzed, including common sleep metrics such as sleep efficiency, sleep onset delay, and sleep stages but also vital signs in the form of heart and breathing rate as well as movements in bed. Association with self-reported health, evaluated by EuroQol visual analog scale (EQ-VAS) ratings, were quantitatively evaluated using individual linear mixed-effects models. Translation to objective, real-world health incidents was investigated through manual retrospective case-by-case analysis.
ResultsUsing EQ-VAS rating based self-reported perceived health, we identified body movements in bed—measured by the number toss-and-turn events—as the most predictive sleep parameter (t score=–0.435, P value [adj]=<.001). Case-by-case analysis further substantiated this finding, showing that increases in number of body movements could often be explained by reported health incidents. Real world incidents included heart failure, hypertension, abdominal tumor, seasonal flu, gastrointestinal problems, and urinary tract infection.
ConclusionsOur results suggest that nightly body movements in bed could potentially be a highly relevant as well as easy to interpret and derive digital biomarker to monitor a wide range of health deteriorations in older adults. As such, it could help in detecting health deteriorations early on and provide timelier, more personalized, and precise treatment options. |
| first_indexed | 2024-12-23T14:54:54Z |
| format | Article |
| id | doaj.art-7d9d060bd6df4b72ba553e4434771523 |
| institution | Directory Open Access Journal |
| issn | 2291-5222 |
| language | English |
| last_indexed | 2024-12-23T14:54:54Z |
| publishDate | 2021-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR mHealth and uHealth |
| spelling | doaj.art-7d9d060bd6df4b72ba553e44347715232022-12-21T17:42:47ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222021-06-0196e2466610.2196/24666Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory StudySchütz, NarayanSaner, HugoBotros, AngelaPais, BrunoSantschi, ValérieBuluschek, PhilippGatica-Perez, DanielUrwyler, PrabithaMüri, René MNef, TobiasBackgroundPopulation aging is posing multiple social and economic challenges to society. One such challenge is the social and economic burden related to increased health care expenditure caused by early institutionalizations. The use of modern pervasive computing technology makes it possible to continuously monitor the health status of community-dwelling older adults at home. Early detection of health issues through these technologies may allow for reduced treatment costs and initiation of targeted preventive measures leading to better health outcomes. Sleep is a key factor when it comes to overall health and many health issues manifest themselves with associated sleep deteriorations. Sleep quality and sleep disorders such as sleep apnea syndrome have been extensively studied using various wearable devices at home or in the setting of sleep laboratories. However, little research has been conducted evaluating the potential of contactless and continuous sleep monitoring in detecting early signs of health problems in community-dwelling older adults. ObjectiveIn this work we aim to evaluate which contactlessly measurable sleep parameter is best suited to monitor perceived and actual health status changes in older adults. MethodsWe analyzed real-world longitudinal (up to 1 year) data from 37 community-dwelling older adults including more than 6000 nights of measured sleep. Sleep parameters were recorded by a pressure sensor placed beneath the mattress, and corresponding health status information was acquired through weekly questionnaires and reports by health care personnel. A total of 20 sleep parameters were analyzed, including common sleep metrics such as sleep efficiency, sleep onset delay, and sleep stages but also vital signs in the form of heart and breathing rate as well as movements in bed. Association with self-reported health, evaluated by EuroQol visual analog scale (EQ-VAS) ratings, were quantitatively evaluated using individual linear mixed-effects models. Translation to objective, real-world health incidents was investigated through manual retrospective case-by-case analysis. ResultsUsing EQ-VAS rating based self-reported perceived health, we identified body movements in bed—measured by the number toss-and-turn events—as the most predictive sleep parameter (t score=–0.435, P value [adj]=<.001). Case-by-case analysis further substantiated this finding, showing that increases in number of body movements could often be explained by reported health incidents. Real world incidents included heart failure, hypertension, abdominal tumor, seasonal flu, gastrointestinal problems, and urinary tract infection. ConclusionsOur results suggest that nightly body movements in bed could potentially be a highly relevant as well as easy to interpret and derive digital biomarker to monitor a wide range of health deteriorations in older adults. As such, it could help in detecting health deteriorations early on and provide timelier, more personalized, and precise treatment options.https://mhealth.jmir.org/2021/6/e24666 |
| spellingShingle | Schütz, Narayan Saner, Hugo Botros, Angela Pais, Bruno Santschi, Valérie Buluschek, Philipp Gatica-Perez, Daniel Urwyler, Prabitha Müri, René M Nef, Tobias Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study JMIR mHealth and uHealth |
| title | Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study |
| title_full | Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study |
| title_fullStr | Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study |
| title_full_unstemmed | Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study |
| title_short | Contactless Sleep Monitoring for Early Detection of Health Deteriorations in Community-Dwelling Older Adults: Exploratory Study |
| title_sort | contactless sleep monitoring for early detection of health deteriorations in community dwelling older adults exploratory study |
| url | https://mhealth.jmir.org/2021/6/e24666 |
| work_keys_str_mv | AT schutznarayan contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT sanerhugo contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT botrosangela contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT paisbruno contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT santschivalerie contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT buluschekphilipp contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT gaticaperezdaniel contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT urwylerprabitha contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT murirenem contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy AT neftobias contactlesssleepmonitoringforearlydetectionofhealthdeteriorationsincommunitydwellingolderadultsexploratorystudy |