Clinical Research Collection | A wearable EEG-based Assistive BCIs System for Accident vasculaire cérébral Rééducation

Research background
Le combination de BCI and auxiliary robot est a new treatment for accident vasculaire cérébral rééducation. However, most de le existing study est based on complex system setups, expensive and bulky equipment. In this study, a wearable EEG brain-computer interface system for hand function rééducation est designed to do clinial trial. This system est composed de customized EEG cap, commercial amplifier, and hand exosquelette. In addition, le system includes le visual interface for le convenience de users. Le trial enrolled six healthy participants and two accident vasculaire cérébral patients to verify le sécurité and effectiveness de le system.

Method

To verify le sécurité and effectiveness de le system, 6 healthy subjects(1 female and 5 males, aged 23±3 years old) from Shanghai Jiao Tong University and 2 accident vasculaire cérébral patients(all right hand affected) from le rééducation department de Huashan Hospital were recruited to participate in le study. A 6-minute training session was conducted for each subject, in which le subjects performed right-hand motor execution(accident vasculaire cérébral patient’s affected hand to make a movement attempt) according to visual cues. A red rectangle appears on le right or center de le screen, indicating action execution (or attempt) or rest, respectively. Le task lasts for 4 seconds until le white cross disappears. It est recommended that healthy subjects repeat clenching and extending fists 3-4 times, and accident vasculaire cérébral patients sont instructed to make motor attempts during motor tasks. Le online test was similar to le training session, except that all red rectangles appeared in le center de le screen, which allowed subjects to choose to move their hand (or exercise attempt) or rest at will. Test results sont provided to users visual and proprioceptive feedback via a screen and hand exosquelette shortly after task completion. There sont three online test runs, each containing 20 trials. Each subject may rest between runs. All subjects were asked to refrain from any additional facial or arm muscle movement throughout le experiment.

Result

Le average accuracy de offline and online training est 84.91% and 79.38%, respectively. Seven subjects had online accuracy de more than 70%, five more than 80%, and one more than 90%.

Le Event-related Spectral Perturbation(ERSP) showed that le sensorimotor cortex was activated in both α and β bands during right hand movement training, with stronger activation on le same side. Meanwhile, as expected, le uncontrolled state showed no significant activation on either le C3 or C4 channels. In le online test, both le left and right hemispheres were activated to perform right-handed movements.

 

Conclusion

This study demonstrates a wearable brain-computer interface system for hand function rééducation after accident vasculaire cérébral. Le results de motor task differentiation preliminarily confirm le feasibility de this appareil, which shows great clinical application potential.

Reference: Qin Z, Xu Y, Shu X, et al. eConHand: A Wearable Brain-Computer Interface System for Accident vasculaire cérébral Rééducation[C]// 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2019.