Parameter Extraction of Muscle Contraction Signals from Children with ASD During Fine Motor Activities

This study was performed to extract meaningful parameters from Muscle contraction (MC) sensor signals, which could be used as biofeedback parameters for children with autism spectrum disorder (ASD) performance during fine motor activities. Four male children with ASD and 2 typical development (TD) male children participated in the experiment. Participants were asked to perform repetitive hand grips on the hand dynamometer while simultaneously recording measurements from the MC sensor on the forearm (flexor digitorum profundis). Because MMG signals are inherently mechanical, signal acquisition can be performed without separate circuitry to eliminate electrical noise interfaces, particularly 50 Hz noise. Handgrip strength using the MC sensor was 0.98 ± 0.69 V in children with ASD and 3.32 ± 0.56 V at TD. Comparison between the measured peak signal MC and hand dynamometer torque revealed a strong linear relationship with a high degree of agreement R = 98%, P < 0.0001. This study demonstrates that the MC sensor can accurately measure the contraction of a small muscle, the flexor digitorum profundis, in children.