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The ageing population of our global society is presenting some new problems. In particular, the rate of dementia is also increasing. People with dementia (PwD) may wander outside the area controlled by the caregivers, which may result in serious accidents, such as traffic accidents. Constant monitoring is therefore required, to enable a fast response to wandering. This round-the-clock monitoring task imposes a heavy burden on caregivers, which can be reduced if reliable systems for automatically monitoring PwD in their homes can be developed. One of the fundamental features to support effective wandering detection systems is the ability to classify the presence or absence of a subject in a designated area. In this paper, we propose a novel system to classify the presence of a person within a designated area using a microwave Doppler sensor. We focus on the detection of bio-signals; in particular, of respiratory and heartbeat signals. The microwave Doppler sensor adopted in this system has two output channels, providing in-phase and quadrature signals. Four types of features are extracted from the observed signals and then input to a support vector machine algorithm, to classify the presence/absence of a subject in the target area. For the presence of a subject, two different states are considered: a rest-state and a moving-state. The rest-state corresponds to a subject quietly sitting in the designated area; the moving-state corresponds to a subject walking randomly within the designated area. The system was evaluated using 11 subjects, and exhibited a 99.73 % accuracy. In particular, the absence of a subject in the area could be detected with 100 % certainty. The obtained experimental results show that considering the bio-signals does, in fact, yield better results.

Automatic Wandering Detection with a Microwave Doppler Sensor: Classification of Human's Presence Using Bio-Information