• Shigeki Kamada, Yuji Matsuo, Sunao Hara and Masanobu Abe,
• ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks (LocalRec), California, USA, Nov. 2017.

Abstract

In this paper, we propose a new monitoring scheme for a person with dementia (PwD). The novel aspect of this monitoring scheme is that the size of the monitoring area changes for different stages of dementia, and the monitoring area is automatically generated using global positioning system (GPS) data collected by the PwD. The GPS data are quantized using the GeoHex code, which breaks down the map of the entire world into regular hexagons. The monitoring area is defined as a set of GeoHex codes, and the size of the monitoring area is controlled by the granularity of hexagons in the GeoHex code. The stages of dementia are estimated by analyzing the monitoring area to determine how frequently the PwD wanders. In this paper, we also examined two aspects of the implementation of the proposed scheme. First, we proposed an algorithm to estimate the monitoring area and evaluate its performance. The experimental results showed that the proposed algorithm can estimate the monitoring area with a precision of 0.82 and recall of 0.86 compared with the ground truth. Second, to investigate privacy considerations, we showed that different persons have different preferences for the granularity of the hexagons in the monitoring systems. The results indicate that the size of the monitoring area also should be changed for PwDs.