| Autor: |
Graham Kelly, Brian Burkhardt, Ou Bai, Ding-Yu Fei, Douglas P. Murphy, John Fox, Javier Soars, William Lovegreen |
| Rok vydání: |
2015 |
| Předmět: |
|
| Zdroj: |
TENCON 2015 - 2015 IEEE Region 10 Conference. |
| DOI: |
10.1109/tencon.2015.7373060 |
| Popis: |
Smooth and convenient user control of prostheses is critical to restore motor and cognitive functions in amputees. This study aims to develop a smart system supporting volitional control of prostheses directly from user' thought without any interface manipulation. An ultra-portable, wireless-enabled, and low powered device prototype was developed to amplify and process multi-channel electroencephalography (EEG) signals in real-time. Signal processing and machine learning algorithms were designed to decode user's volition from EEG signals and subsequently to command prosthetic devices. A feasibility test was conducted on an amputee user with right leg amputation. Preliminary results showed that the amputee user was able to volitionally control a knee-locker installed on the prosthetic leg at a sensitive rate of 83.5% with zero false positive detections in real-time. Future study will be directed to support multifunctional, volitional control of robotic prostheses. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
