Effects of Brain-Computer Interface-Controlled Hand Robot Training on Post-Stroke Recovery of Upper Limb Motor...

Area of Science:

• Neurorehabilitation
• Robotics in Medicine
• Stroke Recovery

Background:

• Stroke significantly impairs motor function, particularly in the upper limbs.
• Traditional rehabilitation methods have limitations in restoring fine motor skills.
• Brain-computer interfaces (BCIs) offer novel therapeutic avenues for neurological recovery.

Purpose of the Study:

• To systematically evaluate the effectiveness of BCI-controlled hand robot training for post-stroke motor rehabilitation.
• To compare BCI-controlled hand robot training against conventional hand robot training and routine rehabilitation.
• To assess the impact on upper limb motor function, proximal and distal limb control, and spasticity.

Main Methods:

• A meta-analysis of 11 randomized controlled trials (RCTs) involving 380 stroke patients.
• Inclusion criteria focused on dose-matched RCTs comparing BCI-controlled hand robot training with control interventions.
• Data were analyzed using RevMan 5.4 software.

Main Results:

• BCI-controlled hand robot training significantly improved Fugl-Meyer Assessment for Upper Extremity (FMA-UE) scores compared to hand robot training alone.
• Significant improvements were observed in proximal upper limb function and a reduction in finger flexor spasticity.
• No significant differences were found in distal upper limb motor function or Action Research Arm Test (ARAT) scores compared to hand robot training alone.
• BCI-controlled hand robot training showed significant improvements in FMA-UE scores compared to routine rehabilitation.

Conclusions:

• BCI-controlled hand robot training is effective in improving overall upper limb and proximal motor function after stroke.
• This intervention can also help alleviate finger flexor spasticity in stroke survivors.
• Further research is needed to confirm efficacy for distal hand function and long-term outcomes.