NDLI: Predicting hand orientation in reach-to-grasp tasks using neural activities from primary motor cortex

Content Provider	IEEE Xplore Digital Library
Author	Peng Zhang Xuan Ma Hailong Huang Jiping He
Copyright Year	2014
Description	Author affiliation: Dept. of Rehabilitation Med., Huazhong Univ. of Sci. & Technol., Wuhan, China (Hailong Huang) \|\| Harrington Dept. of Bioeng., Arizona State Univ., Tempe, AZ, USA (Jiping He) \|\| Neural Interface & Rehabilitation Technol. Res. Center, Huazhong Univ. of Sci. & Technol., Wuhan, China (Peng Zhang; Xuan Ma)
Abstract	Hand orientation is an important control parameter during reach-to-grasp task. In this paper, we presented a study for predicting hand orientation of non-human primate by decoding neural activities from primary motor cortex (M1). A non-human primate subject was guided to do reaching and grasping tasks meanwhile neural activities were acquired by chronically implanted microelectrode arrays. A Support Vector Machines (SVMs) classifier has been trained for predicting three different hand orientations using these M1 neural activities. Different number of neurons were selected and analyzed; the classifying accuracy was 94.1% with 2 neurons and was 100% with 8 neurons. Data from highly event related neuron units contribute a lot to the accuracy of hand orientation prediction. These results indicate that three different hand orientations can be predicted accurately and effectively before the actual movements occurring with a small number of related neurons in M1.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	1306
Ending Page	1309
File Size	832274
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6943838
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Accuracy Grasping Support vector machines Educational institutions Firing Shape
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A study of predicting movement intentions in various spatial reaching tasks from M1 neural activities

Motor Cortical Encoding of Hand Orientation in a 3-D Reach-to-grasp Task

Cell categories and k-nearest neighbor algorithm based decoding of primary motor cortical activity during reach-to-grasp task

Dorsal premotor cortex of the macaque monkey participate grasp planning

Decoding grasp types with high frequency of local field potentials from primate primary dorsal premotor cortex

Reconstructing grasping motions from high-frequency local field potentials in primary motor cortex

Analysis of neural interaction in motor cortex during reach-to-grasp task based on Dynamic Bayesian Networks

Selection of cortical neurons for identifying movement transitions in stand and squat

Optical stimulation of primary motor cortex with 980nm infrared neural stimulation

Predicting hand orientation in reach-to-grasp tasks using neural activities from primary motor cortex

Similar Documents

A study of predicting movement intentions in various spatial reaching tasks from M1 neural activities

Motor Cortical Encoding of Hand Orientation in a 3-D Reach-to-grasp Task

Cell categories and k-nearest neighbor algorithm based decoding of primary motor cortical activity during reach-to-grasp task

Dorsal premotor cortex of the macaque monkey participate grasp planning

Decoding grasp types with high frequency of local field potentials from primate primary dorsal premotor cortex

Reconstructing grasping motions from high-frequency local field potentials in primary motor cortex

Analysis of neural interaction in motor cortex during reach-to-grasp task based on Dynamic Bayesian Networks

Selection of cortical neurons for identifying movement transitions in stand and squat

Optical stimulation of primary motor cortex with 980nm infrared neural stimulation

Predicting hand orientation in reach-to-grasp tasks using neural activities from primary motor cortex