Editors' ChoiceNeuroengineering

Enabling Technology Gives the Brain a Hand

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Science Translational Medicine  09 Mar 2011:
Vol. 3, Issue 73, pp. 73ec33
DOI: 10.1126/scitranslmed.3002338

Our brain processes a vast amount of sensory information and commands the body to generate various outputs, ranging from a head nod to an eloquent speech. However, when the information and command pathways are interrupted as a result of, for example, spinal cord injury or stroke, such expression and independence is reduced, or even lost. Neuroscientists and engineers are now combining efforts to interface the brain with advanced electronic and computer systems. These so-called brain–machine interfaces (BMIs) enable impaired individuals to operate computers or control robotic hands with a simple thought. To develop a BMI with long-term stability and low clinical risk, Yanagisawa et al. explored the use of electrocorticography (ECoG) signals.

ECoG records brain activity using high-resolution cortical surface electrodes. Previous studies have demonstrated that human subjects can use ECoG signals to control a cursor on a computer screen. For this study, the authors applied ECoG signals to control the prosthetic hand, consisting of eight independent tendons capable of grasping movements, of a post-stroke patient in real-time. Sixty platinum-disc electrodes were placed over the sensorimotor cortex in the brain and remained implanted for 2 weeks. Signal powers of three frequency bands (1 to 8, 25 to 40, and 80 to 150 Hz) from all 60 channels were calculated on-the-fly every 200 ms to control the prosthetic hand. When the patient wanted to move, a hybrid of two neural decoders––one to detect intent to move, one to detect type of hand movement––interpreted the ECoG signals. This scheme allowed the participant to control the prosthetic hand with minimal training. In contrast with previous ECoG BMI studies, which were conducted in able-bodied subjects, this study was conducted in a participant who possessed limited hand movement function owing to stroke (thalamic hemorrhage). Thus, the use of ECoG signals for prosthetic limb control in this study represents an important step forward in applying BMI technology to several patient populations with limb paralysis.

T. Yanagisawa et al., Real-time control of a prosthetic hand using human electrocorticography signals. J. Neurosurg. 11 February 2011 (10.3171/2011.1.JNS101421). [Abstract]

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