MUSIC-based Non-contact Heart Rate Estimation with Adaptive Window Size Setting

摘要

Continuous HR (Heart Rate) monitoring enables the stress estimation in daily life. A Doppler sensor could be a key device to facilitate the non-contact HR estimation. As one of the Doppler sensor-based HR estimation methods, we have previously proposed a MUSIC (MUltiple SIgnal Classification)-based HR estimation method. MUSIC is the algorithm widely used as a tool to estimate DOA (Direction of Arrival). In our previous method, MUSIC spectrum is calculated in each sliding window, and then HR is estimated by the maximum peak detection over the MUSIC spectrum. However, when HR changes largely within the window, several peaks due to heartbeats appear over the MUSIC spectrum, which might cause the incorrect peak detection. Hence, an adaptive window is required so that only one peak appears. In this paper, we propose a MUSIC-based HR estimation method with an adaptive window size setting. When several peaks due to heartbeats appear over the MUSIC spectrum, our proposed method shortens the time window and re-calculates the MUSIC spectrum, which is repeated until only one peak appears. The experimental results showed that our method outperformed not only our previous one but also the other existing MUSIC-based HR estimation one in terms of the estimation accuracy of the HR, the stress indexes CVI (Cardiac Vagal Index) and CSI (Cardiac Sympathetic Index).