Towards clinically relevant neural prostheses
Abstract/Contents
- Abstract
- Neural prostheses translate signals from the brain into useful control signals, manipulating end-effectors such as computer cursors or robotic arms. Their aim is to offer greater interaction with the world for patients suffering from limb dysfunction due to spinal cord injury, neurodegenerative disease, and other conditions leading to limb paralysis. Prior intracortical electrode neural prosthesis studies have demonstrated compelling proof-of-concept systems, but barriers to successful clinical translation still remain, such as performance and robustness. Measures of performance include the speed, accuracy, and bitrate of the system. Robustness refers to the sustained performance of the system within a day and across days. The work presented here demonstrates algorithms and advances for neural prostheses that increase both performance and robustness. The recalibrated feedback intention trained Kalman filter (ReFIT-KF) increased performance by at least twofold compared to previously reported decoders, approaching the speed of natural arm movements. It achieved bitrates of up to 4.5 bits per second (bps) and communication rates of up to 10 words per minute (wpm) when used on a typing task. These results were reliable and repeatable for hours at a time across 4 array-years between two subjects. Utilizing neural spike threshold crossings as a signal source, the ReFIT-KF algorithm also demonstrated sustainable performance without any changes to decoder weights for one year with a degradation rate of 0.05 bps per month. Performance further increased when the ReFIT-KF was combined with an HMM state decoder for the detection of clicks, eliminating the need for hold periods. This combined ReFIT-KF and HMM decoder achieved bitrates of up to 6.5 bps and 15 wpm. Taken together, these findings may help advance neural prostheses closer to clinical viability.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2012 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Nuyujukian, Paul Herag |
|---|---|
| Associated with | Stanford University, Department of Bioengineering. |
| Primary advisor | Shenoy, Krishna V. (Krishna Vaughn) |
| Thesis advisor | Shenoy, Krishna V. (Krishna Vaughn) |
| Thesis advisor | Boahen, Kwabena (Kwabena Adu) |
| Thesis advisor | Henderson, Jaimie (Jaimie M.) |
| Advisor | Boahen, Kwabena (Kwabena Adu) |
| Advisor | Henderson, Jaimie (Jaimie M.) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Paul Herag Nuyujukian. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Ph.D. Stanford University 2012 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2012 by Paul Herag Nuyujukian
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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