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SALON: Simplified Sensing System for Activity of Daily Living in Ordinary Home

1
Nara Institute of Science and Technology, Ikoma, Nara 630-0192, Japan
2
RIKEN, Center for Advanced Intelligence Project AIP, Chuo-ku, Tokyo 103-0027, Japan
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(17), 4895; https://doi.org/10.3390/s20174895
Received: 4 August 2020 / Revised: 26 August 2020 / Accepted: 27 August 2020 / Published: 29 August 2020
As aging populations continue to grow, primarily in developed countries, there are increasing demands for the system that monitors the activities of elderly people while continuing to allow them to pursue their individual, healthy, and independent lifestyles. Therefore, it is required to develop the activity of daily living (ADL) sensing systems that are based on high-performance sensors and information technologies. However, most of the systems that have been proposed to date have only been investigated and/or evaluated in experimental environments. When considering the spread of such systems to typical homes inhabited by elderly people, it is clear that such sensing systems will need to meet the following five requirements: (1) be inexpensive; (2) provide robustness; (3) protect privacy; (4) be maintenance-free; and, (5) work with a simple user interface. In this paper, we propose a novel senior-friendly ADL sensing system that can fulfill these requirements. More specifically, we achieve an easy collection of ADL data from elderly people while using a proposed system that consists of a small number of inexpensive energy harvesting sensors and simple annotation buttons, without the need for privacy-invasive cameras or microphones. In order to evaluate the practicality of our proposed system, we installed it in ten typical homes with elderly residents and collected the ADL data over a two-month period. We then visualized the collected data and performed activity recognition using a long short-term memory (LSTM) model. From the collected results, we confirmed that our proposed system, which is inexpensive and non-invasive, can correctly collect resident ADL data and could recognize activities from the collected data with a high recall rate of 72.3% on average. This result shows a high potential of our proposed system for application to services for elderly people. View Full-Text
Keywords: energy harvesting sensor; daily activity recognition; machine learning; simple installation sensing system energy harvesting sensor; daily activity recognition; machine learning; simple installation sensing system
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MDPI and ACS Style

Matsui, T.; Onishi, K.; Misaki, S.; Fujimoto, M.; Suwa, H.; Yasumoto, K. SALON: Simplified Sensing System for Activity of Daily Living in Ordinary Home. Sensors 2020, 20, 4895. https://doi.org/10.3390/s20174895

AMA Style

Matsui T, Onishi K, Misaki S, Fujimoto M, Suwa H, Yasumoto K. SALON: Simplified Sensing System for Activity of Daily Living in Ordinary Home. Sensors. 2020; 20(17):4895. https://doi.org/10.3390/s20174895

Chicago/Turabian Style

Matsui, Tomokazu, Kosei Onishi, Shinya Misaki, Manato Fujimoto, Hirohiko Suwa, and Keiichi Yasumoto. 2020. "SALON: Simplified Sensing System for Activity of Daily Living in Ordinary Home" Sensors 20, no. 17: 4895. https://doi.org/10.3390/s20174895

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