Abstract
With rapid developments in wearable device technology, a vast amount of spatiotemporal data, such as people’s movement and physical activities, are generated. Information derived from the data reveals important knowledge that can contribute a long-term care and psychological assessment of the elders’ living condition especially in long-term care institutions. This study aims to develop a method to investigate the spatial-temporal movement patterns of the elders with their outdoor trajectory information. To achieve the goal, GPS based location data of the elderly subjects from long-term care institutions are collected and analysed with geographic information system (GIS). A GIS statistical model is developed to mine the elderly subjects’ spatiotemporal patterns with the location data and represent their daily movement pattern at particular time. The proposed method first finds the meaningful trajectory and extracts the frequent patterns from the time-stamp location data. Then, a density-based clustering method is used to identify the major moving range and the gather/stay hotspot in both spatial and temporal dimensions. The preliminary results indicate that the major moving area of the elderly people encompasses their dorm and has a short moving distance who often stay in the same site. Subjects’ outdoor appearance are corresponded to their life routine. The results can be useful for understanding elders’ social network construction, risky area identification and medical care monitoring.
Highlights
1.1 General InstructionsAging population has become a global issue
With the rapid development of technology and science, wearable device is popular for application
Sensed data received by geographic information system (GIS) server is the location information of each subject
Summary
1.1 General InstructionsAging population has become a global issue. In Taiwan, according to official survey data, the older population is 12% in 2015. GPS receivers, which are capable of providing information of how often elderly people leave their homes, when they leave their homes, where they travel, how they travel (on foot or in vehicle), and how quickly they move. It offers promise for being able to objectively monitor community mobility in older adults (Krenn et al, 2011). They can collect detailed spatiotemporal information about individual trips away from home that cannot be obtained with existing questionnaires (Webber and Porter, 2009)
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More From: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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