Activity Recognition Using Radio Doppler Effect for Human Monitoring Service

Abstract

Recently it has become more important to monitor the daily human activities of the elderly and of children. In this paper, we propose a system for practical activity recognition using the Doppler effect in 24GHz microwaves. It extracts the features from the signals, selects the optimal features, and then classifies activities using a pattern matching technique. We can sense human activities simply with setting Doppler sensors on the wall or tables, without any body-attached sensors. As a result of performance evaluation, our system achieves over ninety percent in the classification of eight actions on average.