Advanced biofeedback from surface electromyography signals using fuzzy system

The aims of this study were to develop a fuzzy inference-based biofeedback system and investigate its effects when inducing active (shoulder elevation) and passive (relax) pauses on the trapezius muscle electromyographic (EMG) activity during computer work. Surface EMG signals were recorded from clavicular, descending (bilateral) and ascending parts of the trapezius muscles during computer work. The fuzzy system readjusted itself based on the history of previous inputs. The effect of feedback was assessed in terms of muscle activation regularity and amplitude. Active pause resulted in non-uniform muscle activity changes in the trapezius muscle depicted by increase and decrease of permuted sample entropy in ascending and clavicular parts of trapezius, respectively (P <0.05) compared with no pause. Concomitantly, the normalized root mean square of EMG increased approximately 5% in descending part of trapezius bilaterally (P <0.01). These findings confirm that advanced feedback can change the pattern of muscle activation.