AUTHOR=Murphy Douglas P. , Bai Ou , Gorgey Ashraf S. , Fox John , Lovegreen William T. , Burkhardt Brian W. , Atri Roozbeh , Marquez Juan S. , Li Qi , Fei Ding-Yu TITLE=Electroencephalogram-Based Brain–Computer Interface and Lower-Limb Prosthesis Control: A Case Study JOURNAL=Frontiers in Neurology VOLUME=8 YEAR=2017 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2017.00696 DOI=10.3389/fneur.2017.00696 ISSN=1664-2295 ABSTRACT=Objective

The purpose of this study was to establish the feasibility of manipulating a prosthetic knee directly by using a brain–computer interface (BCI) system in a transfemoral amputee. Although the other forms of control could be more reliable and quick (e.g., electromyography control), the electroencephalography (EEG)-based BCI may provide amputees an alternative way to control a prosthesis directly from brain.

Methods

A transfemoral amputee subject was trained to activate a knee-unlocking switch through motor imagery of the movement of his lower extremity. Surface scalp electrodes transmitted brain wave data to a software program that was keyed to activate the switch when the event-related desynchronization in EEG reached a certain threshold. After achieving more than 90% reliability for switch activation by EEG rhythm-feedback training, the subject then progressed to activating the knee-unlocking switch on a prosthesis that turned on a motor and unlocked a prosthetic knee. The project took place in the prosthetic department of a Veterans Administration medical center. The subject walked back and forth in the parallel bars and unlocked the knee for swing phase and for sitting down. The success of knee unlocking through this system was measured. Additionally, the subject filled out a questionnaire on his experiences.

Results

The success of unlocking the prosthetic knee mechanism ranged from 50 to 100% in eight test segments.

Conclusion

The performance of the subject supports the feasibility for BCI control of a lower extremity prosthesis using surface scalp EEG electrodes. Investigating direct brain control in different types of patients is important to promote real-world BCI applications.