A Fully Implantable Brain Machine Interface for Volitional Hand Grasp Restoration in Cervical Quadriplegia. (1st September 2019)

• Record Type: Journal Article
• Authors: Cajigas, Iahn; Prins, Noeline W; Gallo, Sebastian; Naeem, Jasim A; Guerra, Santiago; Parks, Brandon; Palermo, Anne; Wilson, Audrey; Fisher, Letitia; Vanni, Steven; Ivan, Michael E; Prasad, Abhishek; Jagid, Jonathan R
• Is Part Of: Neurosurgery. Volume 66(2010)Supplement 1
• Publication Date: 2019-09-01
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1093/neuros/nyz310_148
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: INTRODUCTION: Neural interface research has been strongly motivated by the need to restore communication and control to the estimated 5.3 million people in the US population which currently suffer from some form of paralysis. We recently enrolled a patient with a chronic traumatic cervical spinal cord injury (C5 ASIA A) to undergo placement of a brain machine interface aimed at restoring unilateral upper distal extremity function (ClinicalTrials.gov NCT02564419). The objective of this study was to evaluate the safety and efficacy of a fully implanted brain machine interface consisting of the Medtronic PC + S and the Bioness H200 hand rehabilitation orthosis for the functional restoration of hand grasp in a patient with cervical quadriplegia. METHODS: A computer task was developed to engage the subject in thinking of either hand movement or rest while electrocorticographic (ECoG) activity was recorded. "Open-loop" trials were used to train various classifiers for predicting "move" or "rest" states based on observations of the ECoG activity. In "closed-loop" experiments, the decoded desired hand state was used to drive functional electrical stimulation of the dominant hand utilizing the Bioness H200 orthosis. Functional performance was measured by a modified Jebson Taylor Hand Function (JTHF) test and range of motion. RESULTS: Movement intent information was decoded with an online accuracy of 88.2% with a tree bagging classifier over 21 sessions. Functional improvement was observed in reduction of the average time to perform subtasks within the JTHF test. CONCLUSION: Our results demonstrate that a fully implanted brain machine interface can be safely implanted and used to reliably decode movement intent from motor cortex allowing for volitional control of hand grasp in a laboratory setting. Further work will aim to allow use of the device in a home setting, a critical step for the widespread use of these approaches to restore motor function in patients living with paralysis.