Detecting Psychological Interventions Using Bilateral Electromyographic Wearable Sensors

Area of Science:

• Neuroscience
• Biomedical Engineering
• Kinesiology

Background:

• Auditory stimuli can influence physiological responses.
• Understanding muscle activation patterns is crucial for rehabilitation and performance.
• Surface electromyography (EMG) provides a non-invasive method to measure muscle activity.

Purpose of the Study:

• To investigate the impact of different auditory stimuli on muscular activation patterns.
• To identify which muscles and features are most sensitive to auditory interventions.
• To explore the potential of muscle activation patterns as biomarkers for neuroadaptive interventions.

Main Methods:

• Utilized wearable surface electromyography (EMG) sensors to record muscle activity from Sternocleidomastoid Muscle (SCM), Cervical Erector Muscle (CEM), Quadricep Muscles (QMs), and Tibialis Muscle (TM).
• Applied four auditory interventions: silence, music, positive reinforcement, and negative reinforcement.
• Analyzed time-domain features, statistical features, Hjorth features, and employed Random Forest classification.

Main Results:

• Distinct muscle responses were observed across interventions, with SCM and CEM being highly sensitive and TM being most active and stimulus-dependent.
• Post hoc analyses revealed significant intervention-specific activations in CEM and TM.
• Random Forest classification demonstrated high accuracy and Area Under the ROC Curve for TM, indicating precise intervention differentiation.

Conclusions:

• Auditory stimuli dynamically modulate muscle activation patterns, particularly in the TM.
• Identified statistical and Hjorth features as potential biomarkers for muscle function monitoring.
• The findings support the development of personalized neuroadaptive interventions for rehabilitation, sports science, ergonomics, and healthcare.