A Flow-Theoretic Multimodal Control Framework Fusing Mental and Physical Engagement for Upper-Limb Rehabilitation

Name: A Flow-Theoretic Multimodal Control Framework Fusing Mental and Physical Engagement for Upper-Limb Rehabilitation
Uploaded: 2026-10-19T19:32:41.013373+00:00
Duration: 646 s
Description: The framework fuses EEG (mental engagement) and sEMG (physical effort) into an adaptive impedance control system for upper-limb rehabilitation. It uses Flow Theory to categorize user states like Flow or Boredom, allowing the robot to adjust assistance dynamically. This resulted in a 71.9% reduction in energy use while nearly quadrupling the time users spent in a 'Flow State.'

The framework fuses EEG (mental engagement) and sEMG (physical effort) into an adaptive impedance control system for upper-limb rehabilitation. It uses Flow Theory to categorize user states like Flow or Boredom, allowing the robot to adjust assistance dynamically. This resulted in a 71.9% reduction in energy use while nearly quadrupling the time users spent in a 'Flow State.'

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