The use of a virtual integration environment for the real-time implementation of neural decode algorithms.
We have developed a virtual integration environment (VIE) for the development of neural prosthetic systems. This paper, the second of two companion articles, describes the use of the VIE as a common platform for the implementation of neural decode algorithms. In this paper, a linear filter decode and a recursive Bayesian algorithm are implemented as separate signal analysis modules of the VIE for the real-time decode of end effector trajectory. The process of implementing each algorithm is described and the real-time behavior as well as computational cost for each algorithm is examined. This is the first report of the real-time implementation of the Mixture of Trajectory Models decode [10]. These real-time algorithms can be easily interfaced with pre-existing modules of the VIE to control simulated and real devices.
Bishop
William
W
The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA. william.bishop@jhuapl.edu
Yu
Byron M
BM
Santhanam
Gopal
G
Afshar
Afsheen
A
Ryu
Stephen I
SI
Shenoy
Krishna V
KV
Vogelstein
R Jacob
RJ
Beaty
James
J
Harshbarger
Stuart
S
D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D008253:Macaca mulatta; D009044:Motor Cortex / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D018511:Systems Integration; D014584:User-Computer Interface