SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation

Area of Science:

• Neuroscience
• Rehabilitation Engineering
• Robotics

Background:

• Motor imagery (MI) based brain-computer interfaces (BCI) are used for post-stroke hand rehabilitation but require extensive user training and often yield initial unsatisfactory results.
• Steady-state visually evoked potentials (SSVEP) offer a non-invasive BCI paradigm as an alternative to MI-BCI for detecting user intention.

Purpose of the Study:

• To investigate the efficacy of a steady-state visually evoked potentials (SSVEP) based brain-computer interface (BCI) controlling a soft robotic glove for post-stroke hand function rehabilitation.

Main Methods:

• A randomized control trial (RCT) involving 30 post-stroke patients divided into three groups: conventional therapy, robotic therapy, and BCI-robotic therapy.
• Clinical assessments including Fugl-Meyer Motor Assessment of the Upper Limb (FMA-UL), Wolf Motor Function Test (WMFT), and Modified Ashworth Scale (MAS) were conducted pre-training, post-training, and at a three-month follow-up.

Main Results:

• The BCI-robotic group exhibited significant improvements in FMA full score, FMA shoulder/elbow, FMA wrist/hand, and WMFT compared to other groups.
• Improvements in FMA scores were significantly correlated with BCI accuracy (r = 0.714, p = 0.032).
• SSVEP-BCI controlled soft robotic glove rehabilitation showed superior results to robotic glove rehabilitation alone and comparable efficacy to MI-BCI robotic hand rehabilitation.

Conclusions:

• Steady-state visually evoked potentials (SSVEP) based BCI controlled soft robotic gloves are feasible and effective for post-stroke hand function rehabilitation.
• This SSVEP-BCI approach provides a viable alternative to MI-BCI for enhancing hand function recovery in stroke survivors.