Personalized brain-computer interfaces for amyotrophic lateral sclerosis

Open Access
- Author:
- Geronimo, Andrew M
- Graduate Program:
- Engineering Science
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- March 06, 2015
- Committee Members:
- Steven Schiff, Dissertation Advisor/Co-Advisor
Zachary Simmons, Committee Member
Patrick James Drew, Committee Member
Rick Owen Gilmore, Committee Member
Bruce Gluckman, Committee Member - Keywords:
- brain-computer interface
electroencephalography
amyotrophic lateral sclerosis - Abstract:
- Brain-computer interfaces (BCIs) are a potential last line of communication for those in the late stages of amyotrophic lateral sclerosis (ALS). Following the precedent seen in the field of personalized medicine, this thesis proposal focuses on tailoring BCI devices to personal factors which influence disease outcomes. These factors include the physical, cognitive, and behavioral presentations of the patient as well as the contributing genetic factors. It is with this type of patient-centered personalization that I aim to establish and improve communication in a larger portion of BCI users. I show that previously unused features reflecting task vigilance can be used to increase BCI speed in certain individuals. I also show that psychological changes associated with ALS, rather than physical symptoms, can affect the desire and ability to use a BCI communication system. Analysis of BCI data indicates a frontal shift and delayed timing of discriminable features during a P300 task for ALS patients. Furthermore, patients with cognitive impairment uniquely benefit from BCI features capturing functional connectivity compared to the traditional power features used in a motor-imagery task. In light of the methods for personalization defined in this work, I provide outlook on possible avenues for future BCI development, along with some thoughts on the ethical guidelines for implementation of these systems as assistive communication tools.