Joint Compression of EEG and EMG Signals for Wireless Biometrics

In this paper, we propose a new method for jointly compressing EEG and EMG biosignals based on the so-called cortico-muscular coherence, a function that takes into account the simultaneous frequency changes of the brain and the muscles activity, and can be used, e.g., to classify different kinds of movement. It is shown that this method increases the achievable compression rate compared to transmitting EEG and EMG samples separately, while trading-off with the accuracy of the classification. This can be exploited in several kinds of life and health applications e.g., motor rehabilitation and drivers attention monitoring; it could be especially useful for low-power wireless technologies, such as Bluetooth Low Energy or IEEE 802.15.6, whose transmission resources are limited.