Rhythm of daily living and detection of atypical days for elderly people living alone as determined with a monitoring system

Abstract

We have developed a system for monitoring the health of elderly people living at home. Infrared and other sensor outputs are collected using a monitoring program installed on a personal computer (PC) in the home at a sampling rate of 1 Hz. Once each day, the data are transferred to a server through the Internet using a cable television (TV) connection. An elderly subject was monitored for a 12-day baseline period and completed a daily questionnaire about her activities. This enabled us to identify the rhythm of daily living (sleeping, 23:00–04:59; getting up/breakfast, 05:00–08:59; indoor activities/going out, 09:00–16:59; and dinner/going to bed, 17:00–22:59) and the average outputs from the sensors in the rooms. The subject was then monitored for a further six months. By identifying sensor output counts outside the limits of mean ±3SD, we were able to detect atypical days. During the six-month monitoring period, 29 atypical days were detected. We suggest that the monitoring system may be effective in tele-rehabilitation.