Abstract
A major goal for brain machine interfaces is to allow patients to control prosthetic devices with high degrees of independent movements. Such devices like robotic arms and hands require this high dimensionality of control to restore the full range of actions exhibited in natural movement. Current BMI strategies fall well short of this goal allowing the control of only a few degrees of freedom at a time. In this paper we present work towards the decoding of 27 joint angles from the shoulder, arm and hand as subjects perform reach and grasp movements. We also extend previous work in examining and optimizing the recording depth of electrodes to maximize the movement information that can be extracted from recorded neural signals.
Original language | English |
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Title of host publication | 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012 |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1757-1760 |
Number of pages | 4 |
ISBN (Print) | 9781424441198 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | International Conference of the IEEE Engineering in Medicine and Biology Society 2012 - Hilton San Diego Bayfront, San Diego, United States of America Duration: 28 Aug 2012 → 1 Sep 2012 Conference number: 34th |
Conference
Conference | International Conference of the IEEE Engineering in Medicine and Biology Society 2012 |
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Abbreviated title | EMBC 2012 |
Country | United States of America |
City | San Diego |
Period | 28/08/12 → 1/09/12 |