| |
|
| |
 |
| Single-unit activities from non-human primates were recorded during individuated flexion and extension of fingers and the wrist. Using non-linear hierarchical filters, flexion and extension of each finger and wrist was decoded with close to 100% accuracy, and as high as 92.5% for combined movements of two fingers. The final decoded output was used to actuate a multi-fingered robotic hand in real-time to play the piano. |
|
| |
|
In our work, we demonstrate how different neural recording signal from motor areas – namely single- and mult-unit activity, local field potentials (LFP), and electrocorticogram (ECoG) – can be used to decode an entire suite of dexterous movements including: individuated flexion/extension of each finger and the wrist, wrist rotation, and grasps. The neural activity is recorded from non-human primate experiments performed at collaborating institutions such as the University of Rochester and Arizona State University. |
| |
|
Our group focuses on developing novel cortical control strategies for asynchronously decoding both the onset of movement as well as the specific movement type. Specifically, we have designed various algorithms using Artificial Neural Networks (ANNs), Recurrent Neural Networks, and Kalman filters to decode final end-point states as well as continuous kinematics of the hand. As more advanced prosthetic limbs become commercially available, this work paves the way for developing real-time, dexterous manipulation of a multi-fingered upper-limb neuroprosthesis under direct neural control. |
| |
 |
Using the event related spectral perturbation (ERSP) of LFP activity in four freq bands, we decoded three dexterous grasps with an average accuracy of 81%. LFPs from electrodes in the hand area showed the largest change in ERSP for the highest freq band (75-170 Hz) while LFPs from electrodes placed more medially in the arm area showed the largest change in ERSP for the lowest freq band (<4 Hz). |
|
| |
 |
Researchers |
 |
|
|
Soumyadipta Acharya, MD, MSE
Vikram Aggarwal, MSE
Mohsen Mollazadeh, MSE
Heather Benz
|
| |
|
Collaborators |
|
|
|
Johns Hopkins Applied Physics Laboratory
Marc H. Schieber, MD, PhD - University of Rochester Medical Center
Nathan Crone, MD - Johns Hopkins School of Medicine (Neurology)
Ralph Etienne-Cummings, PhD - Johns Hopkins University (ECE)
Jiping He, PhD - Arizona State University |
| |
|
Funding |
|
|
|
Defense Advanced Project and Research Agency (DARPA) - contract N66001-06-C-8005
National Science and Engineering Research Council (NSERC) of Canada |
| |
|
Publications |
|
|
|
Mollazadeh M, Aggarwal V, Law A, Davidson A, Schieber MH, Thakor NV, Coherency between Spike and LFP Activity during Fine Hand Movements in M1, Conf Proc IEEE Eng Med Biol Soc on Neural Eng, in press, 2009
Aggarwal V, Acharya S Tenore F, Etienne-Cummings R, Schieber MH, Thakor NV, Asynchronous Decoding of Dexterous Finger Movements using M1 Neurons, IEEE Trans Neural Syst Rehabil Eng,16(1):3-14, 2008
Acharya S, Tenore F, Aggarwal V, Etienne-Cummings R, Schieber MH, Thakor NV, Decoding finger movements using volume-constrained neuronal ensembles in M1, IEEE Trans on Neural Sys and Rehab Eng, 16(1):15-23, 2008
Acharya S, Aggarwal V, Tenore F, Shin HC, Etienne-Cummings R, Schieber MH, Thakor NV, Towards a Brain-Computer Interface for dexterous control of a multi-fingered prosthetic hand, Conf Proc IEEE Eng Med Biol Soc on Neural Eng, 1:200-203, 2007 |
| |
|
| |
|
|
