BLE Beacon-based Activity Monitoring System toward Automatic Generation of Daily Report

Tatsuya Morita, Kenta Taki, Manato Fujimoto, H. Suwa, Yutaka Arakawa, K. Yasumoto
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引用次数: 8

Abstract

As the world's population of senior citizens continues to grow, the burdens on the professionals who care for them (carers) are also increasing. In nursing homes, carers need to make a daily report for each resident aiming to improve his/her quality of life. However, in the present understaffed situation, it is difficult and burdensome for carers to record the resident's activity in detail since each carer needs to take care of several residents at the same time. In this paper, we propose an automatic daily report generation system which can monitor the activity of multiple residents in nursing homes. Knowing that important activities such as toilet, bathing, rehabilitation and so on take place in specific areas in a nursing home, it is possible to record residents' activities by tracking their stay areas and movement between the areas within the day. Our proposed system estimates stay areas of multiple residents by machine learning for RSSI values that are sent from BLE beacons attached to residents and received at BLE scanners deployed over multiple areas, and records activities of the residents determined based on their estimated stay areas. The proposed system can also output a daily report of each resident based on the recorded data. We carried out a five-day experiment with four elderly participants in a nursing home and evaluated activity estimation accuracy by leave-one-person-out cross-validation. As a result, our proposed system achieved the weighted average F-measure of 81.6%.
基于BLE信标的每日报表自动生成活动监控系统
随着世界老年人口的持续增长,照顾他们的专业人员(护理人员)的负担也在增加。在护理院,护理员需要每天为每位住客做一份报告,旨在改善他/她的生活质量。然而,在目前人手不足的情况下,由于每位护工需要同时照顾多名住客,因此要详细记录住客的活动是困难和繁重的。在本文中,我们提出了一种自动生成每日报表的系统,可以监控多个老人在养老院的活动。知道诸如上厕所、洗澡、康复等重要的活动发生在养老院的特定区域,就可以通过跟踪他们在一天内的停留区域和区域之间的移动来记录居民的活动。我们提出的系统通过机器学习来估计多个居民的停留区域,这些RSSI值是从附加在居民身上的BLE信标发送的,并由部署在多个区域的BLE扫描仪接收,并记录根据他们估计的停留区域确定的居民的活动。该系统还可以根据记录的数据输出每个居民的每日报告。我们在一家养老院对四名老年人进行了为期五天的实验,并通过留一人交叉验证来评估活动估计的准确性。结果表明,该系统的加权平均f值为81.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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