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Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle
As a sedentary lifestyle leads to numerous health problems, it is important to keep constant motivation for a more active lifestyle. A large majority of the worldwide population, such as office workers, long journey vehicle drivers and wheelchair users, spends several hours every day in sedentary ac...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5677409/ https://www.ncbi.nlm.nih.gov/pubmed/28972556 http://dx.doi.org/10.3390/s17102269 |
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author | Ma, Congcong Li, Wenfeng Gravina, Raffaele Cao, Jingjing Li, Qimeng Fortino, Giancarlo |
author_facet | Ma, Congcong Li, Wenfeng Gravina, Raffaele Cao, Jingjing Li, Qimeng Fortino, Giancarlo |
author_sort | Ma, Congcong |
collection | PubMed |
description | As a sedentary lifestyle leads to numerous health problems, it is important to keep constant motivation for a more active lifestyle. A large majority of the worldwide population, such as office workers, long journey vehicle drivers and wheelchair users, spends several hours every day in sedentary activities. The postures that sedentary lifestyle users assume during daily activities hide valuable information that can reveal their wellness and general health condition. Aiming at mining such underlying information, we developed a cushion-based system to assess their activity levels and recognize the activity from the information hidden in sitting postures. By placing the smart cushion on the chair, we can monitor users’ postures and body swings, using the sensors deployed in the cushion. Specifically, we construct a body posture analysis model to recognize sitting behaviors. In addition, we provided a smart cushion that effectively combine pressure and inertial sensors. Finally, we propose a method to assess the activity levels based on the evaluation of the activity assessment index (AAI) in time sliding windows. Activity level assessment can be used to provide statistical results in a defined period and deliver recommendation exercise to the users. For practical implications and actual significance of results, we selected wheelchair users among the participants to our experiments. Features in terms of standard deviation and approximate entropy were compared to recognize the activities and activity levels. The results showed that, using the novel designed smart cushion and the standard deviation features, we are able to achieve an accuracy of (>89%) for activity recognition and (>98%) for activity level recognition. |
format | Online Article Text |
id | pubmed-5677409 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-56774092017-11-17 Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle Ma, Congcong Li, Wenfeng Gravina, Raffaele Cao, Jingjing Li, Qimeng Fortino, Giancarlo Sensors (Basel) Article As a sedentary lifestyle leads to numerous health problems, it is important to keep constant motivation for a more active lifestyle. A large majority of the worldwide population, such as office workers, long journey vehicle drivers and wheelchair users, spends several hours every day in sedentary activities. The postures that sedentary lifestyle users assume during daily activities hide valuable information that can reveal their wellness and general health condition. Aiming at mining such underlying information, we developed a cushion-based system to assess their activity levels and recognize the activity from the information hidden in sitting postures. By placing the smart cushion on the chair, we can monitor users’ postures and body swings, using the sensors deployed in the cushion. Specifically, we construct a body posture analysis model to recognize sitting behaviors. In addition, we provided a smart cushion that effectively combine pressure and inertial sensors. Finally, we propose a method to assess the activity levels based on the evaluation of the activity assessment index (AAI) in time sliding windows. Activity level assessment can be used to provide statistical results in a defined period and deliver recommendation exercise to the users. For practical implications and actual significance of results, we selected wheelchair users among the participants to our experiments. Features in terms of standard deviation and approximate entropy were compared to recognize the activities and activity levels. The results showed that, using the novel designed smart cushion and the standard deviation features, we are able to achieve an accuracy of (>89%) for activity recognition and (>98%) for activity level recognition. MDPI 2017-10-03 /pmc/articles/PMC5677409/ /pubmed/28972556 http://dx.doi.org/10.3390/s17102269 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ma, Congcong Li, Wenfeng Gravina, Raffaele Cao, Jingjing Li, Qimeng Fortino, Giancarlo Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle |
title | Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle |
title_full | Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle |
title_fullStr | Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle |
title_full_unstemmed | Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle |
title_short | Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle |
title_sort | activity level assessment using a smart cushion for people with a sedentary lifestyle |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5677409/ https://www.ncbi.nlm.nih.gov/pubmed/28972556 http://dx.doi.org/10.3390/s17102269 |
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