Upper limb sensorimotor restoration through brain–computer interface technology in tetraparesis. (September 2019)

• Record Type: Journal Article
• Authors: Bockbrader, Marcia
• Is Part Of: Current opinion in biomedical engineering. Volume 11(2019)
• Page Start: 85
• Page End: 101
• Publication Date: 2019-09
• Subjects: Brain–computer interfaces -- Upper extremity -- Spinal cord injuries -- Quadriplegia -- Assistive technology; ADLs Activities of Daily Living -- ARAT Action Research Arm Test -- ASIA American Spinal Injury Association -- BBT Box and Block Test -- BCI brain–computer interface -- CRS cortical recording and stimulating -- CUE Capabilities of Upper Extremity -- DNN deep neural network -- DoF degrees of freedom -- ECoG electrocorticography -- EEG electroencephalography -- EOG electrooculography -- ESTIM electrical stimulation -- GRASSP Graded Redefined Assessment of Strength, Sensation and Prehension -- GRT Grasp and Release Test -- LDA linear discriminant analysis -- mARAT Modified Action Research Arm Test -- MEA microelectrode array -- MRCP movement-related cortical potential -- MPL Modular Prosthetic Limb -- PID post-implant day -- QIF-SF Quadriplegia Index of Function- Short Form -- SCI spinal cord injury -- SMR-ERD sensorimotor rhythm event-related desynchronization -- SVM support vector machine -- UPMC University of Pittsburgh Medical Center -- wNSP portable neural signal processor; Biomedical engineering -- Periodicals; 610.28
• DOI: 10.1016/j.cobme.2019.09.002
• Languages: English
• ISSNs: 2468-4511

Abstract

Abstract: For individuals with spinal cord injury, brain–computer interface (BCI) technology offers a means to restore lost sensorimotor function by bridging disrupted neural pathways to reanimate paralyzed limbs. Restoring hand function is a high priority of those with tetraparesis because of the impact that manual dexterity has on independence and quality of life. However, to be useful in daily life, BCI systems need to deliver naturalistic and functional grasp speed, force, and dexterity. In clinical trials, individuals with paralysis have achieved the most dexterous control of grasp using either robotic neuroprosthetics or neuromuscular stimulation orthotics controlled by intracortical BCI systems. Next steps are in progress, with the development of portable components and decoding algorithm optimization to simplify setup and calibration.