Proposal of a Human Heartbeat Detection/Monitoring System Employing Chirp Z-Transform and Time-Sequential Neural Prediction

摘要

Heartbeat signal detection and/or monitoring is very important in the rescue of human beings existing under debris after disasters such as earthquakes as well as in the monitoring of patients in hospital. In this paper, we propose a human heartbeat detection/monitoring system employing chirp Z-transform and a time-sequential prediction neural network. The system is an adaptive radar using 2.5 GHz continuous microwave. The CZT realizes high resolution peak search in the frequency domain. We use a neural network to track adaptively the heartbeat signal which often has frequency fluctuation. The network learns the time-sequential peak frequency online in parallel to the detection and tracking. Even when the heartbeat frequency drifts, the network finds and tracks the heartbeat. Experiments demonstrate that the proposed system has high effectiveness in distinction between person-exist and person-non-exist observations, resulting in successful detection of persons.