Evaluating self-assistance during functional reach with a passive hydrostatic exoskeleton under artificial impairment

Area of Science:

• Neuroscience
• Rehabilitation Engineering
• Motor Control

Background:

• Manual self-assistance in functional tasks may enhance motor recovery and reduce reliance on external aids.
• Complex tasks like object manipulation pose bilateral sensorimotor challenges, potentially limiting motor learning in impaired limbs.
• A passive hydrostatic exoskeleton (hEXO) and dysfunctional electrical stimulation (DFES) were used to simulate impairment and enable self-assistance.

Purpose of the Study:

• To investigate the effects of self-assistance using a passive hydrostatic exoskeleton (hEXO) on motor learning under an artificial impairment.
• To determine if self-assistance accelerates motor performance improvements in a reach-to-grasp task.
• To assess the transfer of motor performance and potential dependency on the hEXO.

Main Methods:

• Twenty neurologically typical adults performed a reach-to-grasp task with induced finger flexion synergy via DFES.
• Experiment 1 evaluated short-term effects of DFES and hEXO.
• Experiment 2 compared a self-assist group (hEXO) with a control group to assess adaptation and transfer.

Main Results:

• DFES significantly increased reach-to-grasp time, simulating a sensorimotor challenge.
• The self-assist group showed faster improvement in reach-to-grasp times compared to controls.
• Motor performance did not decline after removing self-assistance, indicating no dependency.

Conclusions:

• Self-assistance with a passive hEXO accelerated motor performance improvements in an artificial impairment model.
• The approach did not lead to performance dependency on the exoskeleton.
• This method holds potential for promoting upper-limb functional independence in clinical populations.