eprintid: 90
rev_number: 4
eprint_status: archive
userid: 5
dir: disk0/00/00/00/90
datestamp: 2007-02-15
lastmod: 2015-05-29 19:47:10
status_changed: 2009-04-08 16:53:58
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Williams, JF
creators_name: Hek, Geertje
creators_name: Vardy, Alistair
creators_name: Rottschäfer, Vivi
creators_name: van den Berg, Jan Bouwe
creators_name: Hulshof, Joost
title: Mathematical Techniques for Neuromuscular Analysis
ispublished: pub
subjects: medicine
studygroups: esgi52
full_text_status: public
abstract: In the central nervous system, alpha-motor neurons play a key role in the chain that results in muscles producing force. A new non-invasive technique to measure the electrical activity involved with force production called High Density Surface Electromyography (HDsEMG) has been proven to be effective in providing novel clinical information on the way alpha-motor neurons control the muscles. This is important for the monitoring of the progression of certain neuromuscular             disorders such as polio. The result of HDsEMG is, however, very difficult to interpret. In this paper we augment the usefulness of HDsEMG with automated mathematical techniques to aid the Motor Unit Number Estimation (MUNE) problem. Also, we create a stochastic model for the firing behavior of an alpha-motor neuron.
date: 2005-02-04
date_type: published
pages: 19
citation:   Williams, JF and Hek, Geertje and Vardy, Alistair and Rottschäfer, Vivi and van den Berg, Jan Bouwe and Hulshof, Joost  (2005) Mathematical Techniques for Neuromuscular Analysis.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/90/1/muscles.pdf