A mathematical model for source separation of MMG signals recorded with a coupled microphone-accelerometer sensor pair

Recent advances in sensor technology for muscle activity monitoring have resulted in the development of a coupled microphone-accelerometer sensor pair for physiological acoustic signal recording. This sensor can be used to eliminate interfering sources in practical settings where the contamination of an acoustic signal by ambient noise confounds detection but cannot be easily removed [e.g., mechanomyography (MMG), swallowing sounds, respiration, and heart sounds]. This paper presents a mathematical model for the coupled microphone-accelerometer vibration sensor pair, specifically applied to muscle activity monitoring (i.e., MMG) and noise discrimination in externally powered prostheses for below-elbow amputees. While the model provides a simple and reliable source separation technique for MMG signals, it can also be easily adapted to other applications where the recording of low-frequency (<1 kHz) physiological vibration signals is required.