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=Volume 8 - 2017

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.
Methods: A transfemoral amputee subject was trained to activate a knee-unlocking switch through mental imaging 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 (ERD) in electroencephalography (EEG) reached a certain threshold. After achieving more than 90 percent reliability for switch activation by EEG rhythm-feedback training managed in 4 visits with each visit about one and half hours, 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 pilot study consisted of one  participant who has a transfemoral amputation, adequate cognition and the physical capacity to engage in the study. 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.