NDLI: Motor unit conduction velocity distribution estimation from evoked motor responses

Content Provider	IEEE Xplore Digital Library
Author	Ledoux, I. Garcia-Gonzalez, M.-T. Duchene, J. Hogrel, J.-Y.
Copyright Year	1964
Abstract	Action potentials travel along the muscle fibers with a specific conduction velocity that depends on their structural and functional properties. Only the estimation of muscle conduction velocity distribution (MCVD) may be able to depict this propagation heterogeneity. Based on the method proposed by Cummins et al. (Electroenceph Clin Neurophysiol, 46:647-658, 1979) to estimate nerve conduction velocity distribution (NCVD), the present paper proposes a method that modifies the Cummins' approach to make it suitable for MCVD estimation from electrically evoked motor responses. The MCVD estimation algorithm was first assessed by means of simulated signals in order to control all signal features during the optimization process. Simulations showed that estimated distributions were very close to the true ones when taking into account the specificities of the muscle action potential, due to its generation and extinction (MSE divided by 5 on distribution standard deviation). This method was then applied to real signals. Elicited motor responses were recorded on the biceps brachii of healthy subjects either during repeated maximal stimulations at 20 Hz or during increasing intensity stimulations at 1 Hz. MCVD estimates were used to analyze fatigue and motor unit recruitment processes, respectively.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	9
File Size	439274
Starting Page	608
Ending Page	616
File Format	PDF
ISSN	00189294
Volume Number	53
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Muscles Signal processing Fatigue Brain modeling Recruitment Electromyography Cities and towns Life estimation Aging Diseases surface EMG Distribution estimation muscle fiber conduction velocity simulation stimulation
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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 technique to track individual motor unit action potentials in surface EMG by monitoring their conduction velocities and amplitudes

Estimation of Motor Unit Conduction Velocity From Surface EMG Recordings by Signal-Based Selection of the Spatial Filters

Direct On-Line Estimation of Muscle Fiber Conduction Velocity by Surface Electromyography

Estimation of Muscle Fiber Conduction Velocity With a Spectral Multidip Approach

Motor unit conduction velocity distribution estimation: Assessment of two short-term processing methods

Assessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions

Investigation on parametric analysis of dynamic EMG signals by a muscle-structured simulation model

A Microprocessor-Based Polarity Correlator for the On-Line Measurement of Muscle Fiber Conduction Velocity

The electromyogram (EMG) as a control signal for functional neuromuscular stimulation. I. Autoregressive modeling as a means of EMG signature discrimination

Motor unit conduction velocity distribution estimation from evoked motor responses

Similar Documents

A technique to track individual motor unit action potentials in surface EMG by monitoring their conduction velocities and amplitudes

Estimation of Motor Unit Conduction Velocity From Surface EMG Recordings by Signal-Based Selection of the Spatial Filters

Direct On-Line Estimation of Muscle Fiber Conduction Velocity by Surface Electromyography

Estimation of Muscle Fiber Conduction Velocity With a Spectral Multidip Approach

Motor unit conduction velocity distribution estimation: Assessment of two short-term processing methods

Assessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions

Investigation on parametric analysis of dynamic EMG signals by a muscle-structured simulation model

A Microprocessor-Based Polarity Correlator for the On-Line Measurement of Muscle Fiber Conduction Velocity

The electromyogram (EMG) as a control signal for functional neuromuscular stimulation. I. Autoregressive modeling as a means of EMG signature discrimination

Motor unit conduction velocity distribution estimation from evoked motor responses