DocumentCode :
2380081
Title :
Toward a biomimetic, bidirectional, brain machine interface
Author :
Fagg, Andrew H. ; Hatsopoulos, Nicholas G. ; London, Brian M. ; Reimer, Jacob ; Solla, Sara A. ; Wang, Di ; Miller, Lee E.
Author_Institution :
Sch. of Comput. Sci., Univ. of Oklahoma, Norman, OK, USA
fYear :
2009
fDate :
3-6 Sept. 2009
Firstpage :
3376
Lastpage :
3380
Abstract :
The interest in Brain Machine Interface (BMI) systems has increased tremendously in recent times; many groups have become involved in this type of research, and progress has been quite encouraging. However, two fundamental limitations remain: 1) With a few notable exceptions, BMIs extract only kinematic information from the brain, ignoring the wealth of force or kinetic information also present in the primary motor cortex, and 2) most existing BMIs depend exclusively on natural vision to guide movement, lacking the rapid proprioceptive feedback that is critical for normal movement. The work reported here describes our efforts to address both of these limitations.
Keywords :
Wiener filters; biocontrol; biomimetics; brain-computer interfaces; feedforward; neurophysiology; signal processing; somatosensory phenomena; biomimetic bidirectional BMI; brain-machine interface; force information; kinematic information; kinetic information; natural vision; primary motor cortex; rapid proprioceptive feedback; Algorithms; Biomechanics; Biomimetics; Brain; Equipment Design; Humans; Kinetics; Man-Machine Systems; Models, Statistical; Motor Cortex; Movement; Robotics; Torque; User-Computer Interface; Vision, Ocular;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
ISSN :
1557-170X
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2009.5332819
Filename :
5332819
Link To Document :
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