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Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

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Combining FES and Exoskeletons in a Hybrid Haptic System for Enhancing VR Experience.

L Buatier de Mongeot, E Galofaro, F Ramadan

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society

|November 16, 2023

Summary

This study introduces a hybrid controller merging upper-limb exoskeletons with functional electrical stimulation (FES) to improve motor function rehabilitation. The system enhances haptic feedback, showing promise for treating neuromuscular diseases.

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Area of Science:

Biomedical Engineering
Rehabilitation Technology
Neuroscience

Background:

Robotic technology and functional electrical stimulation (FES) are effective for restoring motor functions in individuals with neuromuscular diseases.
Current rehabilitation methods can be enhanced by integrating advanced control systems for better haptic feedback.

Purpose of the Study:

To develop and test a novel hybrid controller integrating an upper-limb exoskeleton with FES for improved haptic feedback during task-oriented movements.
To evaluate the controller's performance in a virtual environment, focusing on enhancing motor task execution and perceived load.

Main Methods:

A hybrid controller combining an upper-limb exoskeleton with FES was developed and tested on eight unimpaired participants.
Two control modalities, assistive and resistive, were used to modulate perceived load, with real-time adjustment of FES intensity based on limb motion.
Performance was assessed by measuring kinematic error and motion smoothness during virtual pick-and-place tasks.

Main Results:

The hybrid control system significantly reduced target matching error in both assistive and resistive modalities (0.048±0.007 m to 0.06±0.006 m).
Motion smoothness was maintained (SPARC values from -2.58±0.12 to -3.30±0.13) across hybrid conditions.
The resistive approach increased metabolic consumption (1.04±0.03 W/kg), suggesting a more realistic simulation of object weight via FES.

Conclusions:

The developed hybrid controller effectively improves kinematic performance and enhances haptic feedback during upper-limb manipulation tasks.
The system's ability to modulate muscular activation and perceived load shows potential for clinical applications in the rehabilitation of neuromuscular diseases.