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Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults

Background: Home monitoring sensor systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. The aim of this study was to deliver a proof-of-concept for the use of multimodal sensor systems with pervasive computing technology for the detection of cli...

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Autores principales: Saner, Hugo, Schütz, Narayan, Botros, Angela, Urwyler, Prabitha, Buluschek, Philipp, du Pasquier, Guillaume, Nef, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373719/
https://www.ncbi.nlm.nih.gov/pubmed/32760739
http://dx.doi.org/10.3389/fcvm.2020.00110
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author Saner, Hugo
Schütz, Narayan
Botros, Angela
Urwyler, Prabitha
Buluschek, Philipp
du Pasquier, Guillaume
Nef, Tobias
author_facet Saner, Hugo
Schütz, Narayan
Botros, Angela
Urwyler, Prabitha
Buluschek, Philipp
du Pasquier, Guillaume
Nef, Tobias
author_sort Saner, Hugo
collection PubMed
description Background: Home monitoring sensor systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. The aim of this study was to deliver a proof-of-concept for the use of multimodal sensor systems with pervasive computing technology for the detection of clinically relevant health problems over longer time periods. Methods: Data were collected with a longitudinal home monitoring study in Switzerland (StrongAge Cohort Study) in a cohort of 24 old and oldest-old, community-dwelling adults over a period of 1 to 2 years. Physical activity in the apartment, toilet visits, refrigerator use, and entrance door openings were quantified using a commercially available passive infrared motion sensing system (Domosafety S.A., Switzerland). Heart rate, respiration rate, and sleep quality were recorded with the commercially available EMFIT QS bed sensor device (Emfit Ltd., Finland). Vital signs and contextual data were collected using a wearable sensor on the upper arm (Everion, Biovotion, Switzerland). Sensor data were correlated with health-related data collected from the weekly visits of the seniors by health professionals, including information about physical, psychological, cognitive, and behavior status, health problems, diseases, medication, and medical diagnoses. Results: Twenty of the 24 recruited participants (age 88.9 ± 7.5 years, 79% females) completed the study; two participants had to stop their study participation because of severe health deterioration, whereas two participants died during the course of the study. A history of chronic disease was present in 12/24 seniors, including heart failure, heart rhythm disturbances, pulmonary embolism, severe insulin-dependent diabetes, and Parkinson's disease. In total, 242,232 person-hours were recorded. During the monitoring period, 963 health status records were reported and repeated clinical assessments of aging-relevant indicators and outcomes were performed. Several episodes of health deterioration, including heart failure worsening and heart rhythm disturbances, could be captured by sensor signals from different sources. Conclusions: Our results indicate that monitoring of seniors with a multimodal sensor and pervasive computing system over longer time periods is feasible and well-accepted, with a great potential for detection of health deterioration. Further studies are necessary to evaluate the full range of the clinical potential of these findings.
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spelling pubmed-73737192020-08-04 Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults Saner, Hugo Schütz, Narayan Botros, Angela Urwyler, Prabitha Buluschek, Philipp du Pasquier, Guillaume Nef, Tobias Front Cardiovasc Med Cardiovascular Medicine Background: Home monitoring sensor systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. The aim of this study was to deliver a proof-of-concept for the use of multimodal sensor systems with pervasive computing technology for the detection of clinically relevant health problems over longer time periods. Methods: Data were collected with a longitudinal home monitoring study in Switzerland (StrongAge Cohort Study) in a cohort of 24 old and oldest-old, community-dwelling adults over a period of 1 to 2 years. Physical activity in the apartment, toilet visits, refrigerator use, and entrance door openings were quantified using a commercially available passive infrared motion sensing system (Domosafety S.A., Switzerland). Heart rate, respiration rate, and sleep quality were recorded with the commercially available EMFIT QS bed sensor device (Emfit Ltd., Finland). Vital signs and contextual data were collected using a wearable sensor on the upper arm (Everion, Biovotion, Switzerland). Sensor data were correlated with health-related data collected from the weekly visits of the seniors by health professionals, including information about physical, psychological, cognitive, and behavior status, health problems, diseases, medication, and medical diagnoses. Results: Twenty of the 24 recruited participants (age 88.9 ± 7.5 years, 79% females) completed the study; two participants had to stop their study participation because of severe health deterioration, whereas two participants died during the course of the study. A history of chronic disease was present in 12/24 seniors, including heart failure, heart rhythm disturbances, pulmonary embolism, severe insulin-dependent diabetes, and Parkinson's disease. In total, 242,232 person-hours were recorded. During the monitoring period, 963 health status records were reported and repeated clinical assessments of aging-relevant indicators and outcomes were performed. Several episodes of health deterioration, including heart failure worsening and heart rhythm disturbances, could be captured by sensor signals from different sources. Conclusions: Our results indicate that monitoring of seniors with a multimodal sensor and pervasive computing system over longer time periods is feasible and well-accepted, with a great potential for detection of health deterioration. Further studies are necessary to evaluate the full range of the clinical potential of these findings. Frontiers Media S.A. 2020-07-15 /pmc/articles/PMC7373719/ /pubmed/32760739 http://dx.doi.org/10.3389/fcvm.2020.00110 Text en Copyright © 2020 Saner, Schütz, Botros, Urwyler, Buluschek, du Pasquier and Nef. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Saner, Hugo
Schütz, Narayan
Botros, Angela
Urwyler, Prabitha
Buluschek, Philipp
du Pasquier, Guillaume
Nef, Tobias
Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults
title Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults
title_full Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults
title_fullStr Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults
title_full_unstemmed Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults
title_short Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults
title_sort potential of ambient sensor systems for early detection of health problems in older adults
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373719/
https://www.ncbi.nlm.nih.gov/pubmed/32760739
http://dx.doi.org/10.3389/fcvm.2020.00110
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