J.-S. Shieh, C.-T. Chuang, X. Wang, and P.-Y. Kuo (Taiwan)
Human behaviour, automatic monitoring system, PIC microprocessors, frequency and rank order statistics, and monitoring mobility changes
This study describes a way to monitor human behaviour during daily life to diagnose possible health problems through changes in living patterns. Human behaviour reflects the mental and physical health of the subject. Hence, an automatic monitoring system, where activities were monitored by infrared positioning sensors, was developed. In addition, the use of PIC microprocessors, which have fast operation, low power, low cost and web server function, has been designed into our system. Therefore, an embedded box has been designed as a passive monitoring system where data is gathered from a number of physically distributed sensor points within the house, linked using the main wiring as the communications medium, and then automatically transmitted signals using either RS232 wireless (i.e., ratio frequency (RF)) protocol or PICDEM.NET via a TCP/IP interface to the internet into a monitoring and supervisory centre. Moreover, the application of frequency and rank order statistics for monitoring mobility changes of the elderly in their residence is also proposed in this paper. The preliminary study has been tested successfully in a nursing home for two different types of elderly person for six weeks, and in a volunteer’s research room for four weeks. We have found that the average distances and change distances (i.e., Distance) using tools from frequency and rank order statistics can act as an important index for diagnosis of their living pattern and possible health problems.
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