Periodic average magnitude difference function for remote heart rate monitoring

Abstract

Abstract With the increasing attention on remote monitoring of human heart rate by radar, there is a need to develop a method that can estimate heart rate quickly and reliably. In this study, a new estimation method using a periodic average magnitude difference function (PAMDF) is proposed to estimate the heart rate from the radar signal. PAMDF advances the classical average magnitude difference function (AMDF) with the help of maximum likelihood (ML) theory. It operates in the time domain and estimates the heart rate by calculating the signal magnitude difference between all heartbeat periods. The proposed technique is more accurate than AMDF and has a similar performance to the ML estimation, while maintaining the low complexity advantage of AMDF. The algorithm was validated using radar data from two publicly available datasets.

Keywords

• health care
• maximum likelihood estimation
• radar applications
• signal processing