Method for Blink Detection in Single Channel of Invasive Electromyogram Signal

Abstract

Problem statement. Facial nerve damage is the cranial nervous system disorder often leading to facial muscle paralysis, which might be effectively restored using functional electrical stimulation of the fully or partially denervated circular muscle of the eye to achieve muscle contraction to close the eyelids. To control the invasive stimulation system, the automated detection of the blink event in the intact eye is used as a trigger. To achieve this, the new approach to single channel invasive electromyogram (EMG) signal analysis is proposed. Materials and Methods. The combined time-spectral approach to blink detection consists of the two stages, starting from the thresholding of filtered EMG signals in the sliding window, which is followed by comparing the total spectral power in the Fourier domain to minimum and maximum thresholds. If both conditions are met, the EMG in the current window is considered to contain the blink event. In the experiment, the EMG data recorded from the one male adult healthy volunteer is used, the signal contained an acceptable amount of artefacts and was recognized as reflecting the usual EMG. The true positive rate (TPR), positive predictive value (PPV), False Discovery Rate (FDR), and False Negative Rate (FNR) is used as a performance metrics. Results. In the result of applying the proposed blink detection algorithm with 500 ms duration of the time window and 100 ms overlap, the following performance metrics are obtained: TPR = 93%, PPV = 63%, FDR =7%, FNR = 37%. Impact. Acceptable true positive rate of blink detection suggests the method is promising for wider applications in the clinical settings and might be incorporated in the prototypes of implanted systems for facial muscle paralysis restoration using functional electrical stimulation for further development.