Abstract

Spinal cord injury (SCI) frequently results in complete, permanent paralysis. Although it is possible to reverse the effects of incomplete paralysis, complete paralysis effects are permanent. At present, there is no cure for SCI, but engineers can bypass the spinal cord and restore the connection from the brain to the muscles through brain-machine or brain-computer interfaces (BMIs or BCIs). These experiments initially began with rodents and non-human primates (NHPs), which were trained to move cursors, joysticks or robots with their minds beginning in the 20th century. Research progressed to human clinical trials in the late 20th century. In this paper, I present the work done to train a new NHP model for behavioural experiments, how these NHPs were trained, and the neurophysiology involved in training BMI algorithms. With this knowledge, we then moved to non-invasive human clinical trials, in which 8 SCI and 6 control subjects were able to control the opening and closing of their hands with a BCI system using electroencephalographic (EEG) signals from the motor cortex. Finally, we used these algorithms with a SCI subject in an invasive human clinical trial. The subject successfully completed activities of daily living (ADLs) and was able to control an ambulatory device that enabled him to walk upright. The overall accuracy for the BMI was approximately 90% for the upper extremity task and 85% for the lower extremity task. In addition, the subject improved in performance and speed on the Jebsen Hand Function Test (JHFT) during the 20 weeks of the study. Our subject was then sent home with a mechanical glove to continue performing upper-extremity ADLs in the home environment.

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