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Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study

BACKGROUND: Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand bey...

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Autores principales: Sahu, Kirti Sundar, Oetomo, Arlene, Morita, Plinio Pelegrini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718086/
https://www.ncbi.nlm.nih.gov/pubmed/33216001
http://dx.doi.org/10.2196/21016
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author Sahu, Kirti Sundar
Oetomo, Arlene
Morita, Plinio Pelegrini
author_facet Sahu, Kirti Sundar
Oetomo, Arlene
Morita, Plinio Pelegrini
author_sort Sahu, Kirti Sundar
collection PubMed
description BACKGROUND: Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes. OBJECTIVE: The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual’s movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring. METHODS: We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods. RESULTS: The results showed a significant Spearman rank correlation coefficient of 0.8 (P<.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada. CONCLUSIONS: The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home.
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spelling pubmed-77180862020-12-09 Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study Sahu, Kirti Sundar Oetomo, Arlene Morita, Plinio Pelegrini JMIR Mhealth Uhealth Original Paper BACKGROUND: Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes. OBJECTIVE: The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual’s movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring. METHODS: We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods. RESULTS: The results showed a significant Spearman rank correlation coefficient of 0.8 (P<.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada. CONCLUSIONS: The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home. JMIR Publications 2020-11-20 /pmc/articles/PMC7718086/ /pubmed/33216001 http://dx.doi.org/10.2196/21016 Text en ©Kirti Sundar Sahu, Arlene Oetomo, Plinio Pelegrini Morita. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 20.11.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Sahu, Kirti Sundar
Oetomo, Arlene
Morita, Plinio Pelegrini
Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study
title Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study
title_full Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study
title_fullStr Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study
title_full_unstemmed Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study
title_short Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study
title_sort enabling remote patient monitoring through the use of smart thermostat data in canada: exploratory study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718086/
https://www.ncbi.nlm.nih.gov/pubmed/33216001
http://dx.doi.org/10.2196/21016
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