Publication Date

Summer 2021

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Engineering

Advisor

Guna Selvaduray

Keywords

brain-computer interface, brain-machine interface, neural interface, neurotechnology

Subject Areas

Biomedical engineering; Neurosciences

Abstract

Brain-computer interfaces (BCI) improve the quality of life for patients with severe motor disabilities and sensory impairment by providing them a direct way to communicate with the outside world through computers. To gain higher temporal resolution for better devices, intracortical neural electrodes, such as microwire arrays, are used. Microwire electrode arrays bonded to CMOS sensors, for intracortical neural recordings, have been claimed to be scalable. Microwire electrode arrays of varying diameters and densities were constructed and evaluated for percentage connectivity after interfacing with a custom-made CMOS sensor. The results demonstrate that there is no significant difference in the mean connectivity between a 3 mm and a 12 mm bundle as well as between arrays that have a wire-to-wire distance of 200 μm versus 100 μm, confirming the scalability of microwire electrode arrays. Understanding array scalability allows for better electrodes to be built for higher resolution neural recordings, which can help those who suffer from motor or sensory disabilities regain a better quality of life by re-establishing some independence.

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