Brain-machine interfaces use brain signals to control electronic devices. Dr. Marquez Chin's research explores how this technology can be used to assist individuals with limited mobility, and to diagnose, treat and rehabilitate different neurological conditions. The brain-machine interfaces developed in his laboratory can identify different hand and arm movements through detailed analysis of the electrical activity of the brain. These signals can be recorded from a person's scalp or intracranially. Controlling computers, neuroprosthetic devices and robots to restore movement after paralysis are an integral part of Dr. Marquez Chin's research.
César Márquez Chin
Functional electrical stimulation therapy for severe hemiplegia: Randomized control trial revisited.
Can J Occup Ther. 2017 Jan 01;:8417416668370
Eur J Transl Myol. 2016 Jun 13;26(3):6222
EEG-Triggered Functional Electrical Stimulation Therapy for Restoring Upper Limb Function in Chronic Stroke with Severe Hemiplegia.
Case Rep Neurol Med. 2016;2016:9146213
Real-time two-dimensional asynchronous control of a computer cursor with a single subdural electrode.
J Spinal Cord Med. 2012 Sep;35(5):382-91
Healthc Pap. 2009;9(3):51-5 discussion 60-2
Control of a neuroprosthesis for grasping using off-line classification of electrocorticographic signals: case study.
Spinal Cord. 2009 Nov;47(11):802-8
Identification of arm movements using correlation of electrocorticographic spectral components and kinematic recordings.
J Neural Eng. 2007 Jun;4(2):146-58
Scientist, Toronto Rehabilitation Institute (TRI)