Spectral Binning Approach to Classification of Non-Sedentary Human Activity

This paper proposes a spectral binning method for the classification of locomotion and extraneous body motion (EBM) that may occur during Continuous Wave (CW) Doppler radar motion sensing of human subjects. The method analyzes the spectral content of the arctangent demodulated displacement signature, generating an activity classification based on the magnitude of the spectral content for each of several frequency bins. The choice and number of bins used for the overall classification of data were determined by analyzing experimental data. The method successfully classified sedentary, EBM, and locomotion states for 5 subjects. The method can be used both for determining the presence and type of activity, and for recognizing when data segments are not suitable for monitoring sedentary vital signs.