Electrocorticographic control of a prosthetic arm in paralyzed patients
Version of Record online: 2 NOV 2011
Copyright © 2011 American Neurological Association
Annals of Neurology
Volume 71, Issue 3, pages 353–361, March 2012
How to Cite
Yanagisawa, T., Hirata, M., Saitoh, Y., Kishima, H., Matsushita, K., Goto, T., Fukuma, R., Yokoi, H., Kamitani, Y. and Yoshimine, T. (2012), Electrocorticographic control of a prosthetic arm in paralyzed patients. Ann Neurol., 71: 353–361. doi: 10.1002/ana.22613
- Issue online: 23 MAR 2012
- Version of Record online: 2 NOV 2011
- Accepted manuscript online: 19 AUG 2011 02:34PM EST
- Manuscript Accepted: 12 AUG 2011
- Manuscript Revised: 4 AUG 2011
- Manuscript Received: 4 FEB 2011
- Strategic Research Program for Brain Sciences of Ministry of Education, Culture, Sports, Science and Technology-Japan (MEXT). Grant Number: KAKENHI (22700435)
- Nissan Science Foundation
- Ministry of Health, Labor, and Welfare. Grant Number: 18261201
- Strategic Information and Communications R&D promotion Programme (SCOPE), SOUMU
Paralyzed patients may benefit from restoration of movement afforded by prosthetics controlled by electrocorticography (ECoG). Although ECoG shows promising results in human volunteers, it is unclear whether ECoG signals recorded from chronically paralyzed patients provide sufficient motor information, and if they do, whether they can be applied to control a prosthetic.
We recorded ECoG signals from sensorimotor cortices of 12 patients while they executed or attempted to execute 3 to 5 simple hand and elbow movements. Sensorimotor function was severely impaired in 3 patients due to peripheral nervous system lesion or amputation, moderately impaired due to central nervous system lesions sparing the cortex in 4 patients, and normal in 5 patients. Time frequency and decoding analyses were performed with the patients' ECoG signals.
In all patients, the high gamma power (80–150Hz) of the ECoG signals during movements was clearly responsive to movement types and provided the best information for classifying different movement types. The classification performance was significantly better than chance in all patients, although differences between ECoG power modulations during different movement types were significantly less in patients with severely impaired motor function. In the impaired patients, cortical representations tended to overlap each other. Finally, using the classification method in real time, a moderately impaired patient and 3 nonparalyzed patients successfully controlled a prosthetic arm.
ECoG signals appear useful for prosthetic arm control and may provide clinically feasible motor restoration for patients with paralysis but no injury of the sensorimotor cortex. ANN NEUROL 2012;