Abstract
Keeping fully abreast of a patient’s daily health state is an important part of care planning and risk management. However,
comprehensive assis tive technology capable of collecting the data necessary for analyzing the daily health state of patients, while
simultaneously monitoring other aspects their safety and security, has not yet been established. In this paper, we report on the
development of two measurement systems that allow healthcare staff to more easily monitor patients within a nursing home. One
is a system that measures a patient’s head location on a bed (and in the bedside vicinity) via a Microsoft Kinect sensor. This
system is capable of robust head location measurements via the A da Boost-based head recognition algorithm and a random
sampling consent bed recognition algorithm. The other location system tracks a patient’s indoor location within
the nursing home via radio frequency identification tags. To confirm the effectiveness of these systems, we installed the
proposed patient location monitoring system in an actual Tokyo nursing home and the head location tracking system in a
simulated bedside environment created inside our laboratory.