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Detecting Psychological Interventions Using Bilateral Electromyographic Wearable Sensors.

Yedukondala Rao Veeranki1, Sergi Garcia-Retortillo2, Zacharias Papadakis3

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Summary
This summary is machine-generated.

Auditory stimuli significantly alter muscle activation patterns, with the Tibialis Muscle (TM) showing the most stimulus-dependent responses. These findings support personalized neuroadaptive interventions in rehabilitation and sports science.

Keywords:
auditory stimuliclassificationpsychological interventionssurface electromyographywearable sensors

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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.