A Real-Time Brain-Machine Interface Combining Motor Target and Trajectory Intent Using an Optimal Feedback Control Design
Real-time brain-machine interfaces (BMI) have focused on either estimating the continuous movement trajectory or target intent. However, natural movement often incorporates both. Additionally, BMIs can be modeled as a feedback control system in which the subject modulates the neural activity to move...
Main Authors: | Modir Shanechi, Maryam, Williams, Ziv M., Hu, Rollin, Powers, Marissa, Wornell, Gregory W, Brown, Emery Neal |
---|---|
Other Authors: | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
Format: | Article |
Language: | en_US |
Published: |
Public Library of Science
2013
|
Online Access: | http://hdl.handle.net/1721.1/79700 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0001-9166-4758 |
Similar Items
-
Neural population partitioning and a concurrent brain-machine interface for sequential motor function
by: Hu, Rollin, et al.
Published: (2014) -
A parallel point-process filter for estimation of goal-directed movements from neural signals
by: Modir Shanechi, Maryam, et al.
Published: (2012) -
Real-time brain-machine interface architectures : neural decoding from plan to movement
by: Modir Shanechi, Maryam
Published: (2012) -
Comparison of practical feedback algorithms for multiuser MIMO
by: Modir Shanechi, Maryam, et al.
Published: (2011) -
Universal codes for parallel Gaussian channels
by: Modir Shanechi, Maryam
Published: (2011)