by PNAS Nexus

A man uses the RehabSwift personalized brain-computer interface therapy system. Credit: RehabSwift Pty Ltd A setup of the neurofeedback training sessions for a typical participant whose right side is affected by stroke. (a) The EEG cap records EEG signals. (b) The EEG amplifier receives and amplifies the EEG signals and then sends them to a laptop PC for processing. (c) The PC processes the EEG signals and accordingly commands the orthoses. (d) The right orthosis provides proprioceptive feedback during MI. (e) The free-running left orthosis provides visual feedback during relaxation. Note that for participants with an affected left side, their left hand would be engaged with the left orthosis instead. PC, personal computer. PNAS Nexus (2024). DOI: 10.1093/pnasnexus/pgae240

A personalized brain-computer interface therapy, RehabSwift, significantly enhances hand mobility for stroke survivors. Strokes often lead to impaired hand function, presenting substantial challenges in daily activities. Sam Darvishi and colleagues developed and tested a brain-computer interface therapy that translates imagined hand movements into real actions using a personalized algorithm and bionic hands.

The study involved twelve chronic stroke survivors from South Australia who had limited use of their arms but retained clear thinking abilities. Throughout 18 sessions, participants used the RehabSwift system, which included a special cap that measured their brain activity.

Participants imagined moving their fingers, and this brain activity was then translated into actual finger movements by bionic hands providing both visual and physical feedback. Participants showed improvements in various areas, including overall arm function, hand movement tests, reaction times, and hand strength. These gains were maintained at follow-up assessments 4–6 weeks after training.

Many participants reported achieving their mobility goals after the training. According to the authors, these findings highlight the potential of brain-computer interfaces as powerful, personalized, and adaptable tools for stroke rehabilitation.

The study is published in the journal PNAS Nexus.

More information: Darvisihi et al. Enhancing poststroke hand movement recovery: Efficacy of RehabSwift, a personalized brain–computer interface system, PNAS Nexus (2024). DOI: 10.1093/pnasnexus/pgae240, academic.oup.com/pnasnexus/art … /3/7/pgae240/7709513

Journal information: PNAS Nexus 

Provided by PNAS Nexus