Design and Implementation of a Rehabilitation Upper-limb Exoskeleton Robot Controlled by Cognitive and Physical...

Area of Science:

• Rehabilitation Engineering
• Human-Robot Interaction
• Neuroscience

Background:

• Neurological injuries impair motor function, necessitating innovative rehabilitation strategies.
• Activating neuroplasticity is crucial for recovery, requiring engaging and effective therapeutic tools.
• Existing rehabilitation devices often lack intuitive user interaction and patient-centered design.

Purpose of the Study:

• To present an upper limb exoskeleton designed for neuroplasticity activation in neurological injury rehabilitation.
• To enable both cognitive (via electromyography signals) and physical (via load cell sensors) user interaction.
• To implement a user-centered design process (ISO9241-210:2010) for enhanced patient acceptance.

Main Methods:

• Utilized ISO9241-210:2010 for a human-centered exoskeleton design process.
• Collected design requirements from usability tests and literature reviews.
• Developed and evaluated a hybrid admittance control system using electromyography and load cell sensor inputs for active therapy, alongside evaluating electromyography signal classification models.

Main Results:

• The proposed hybrid admittance control system effectively integrates cognitive and physical inputs for active rehabilitation exercises.
• The system is easily implemented and does not require complex musculoskeletal modeling.
• Evaluated electromyography signal classification models identified optimal settings for cognitive human-robot interaction.

Conclusions:

• The developed upper limb exoskeleton offers a promising approach for enhancing neuroplasticity through interactive rehabilitation.
• The hybrid admittance control provides a flexible and accessible method for active therapy in neurological rehabilitation.
• The user-centered design methodology contributes to improved patient acceptance and engagement in the rehabilitation process.