Abstract
Objective: Motor unit loss associated with neuropathic disorders affects motor unit activation. Quantitative electromyographic (EMG) features of motor unit activation estimated from the sequences of motor unit potentials (MUPs) created by concurrently active motor units can support the detection of neuropathic disorders. Interpretation of most motor unit activation feature values are, however, confounded by uncertainty regarding the level of muscle activation during EMG signal detection. A set of new features circumventing these limitations are proposed, and their utility in detecting neuropathy is investigated using simulated and clinical EMG signals. Methods: The firing sequence of a motor neuron was simulated using a compartmentalized Hodgkin-Huxley based model. A pool of motor neurons was modelled such that each motor neuron was subjected to a common level of activation. The detection of the firing sequence of a motor neuron using a clinically detected EMG signal was simulated using a model of muscle anatomy combined with a model representing muscle fiber electrophysiology and the voltage detection properties of a concentric needle electrode. Significance: Findings are based on simulated EMG data representing 30 normal and 30 neuropathic muscles as well as clinical EMG data collected from the tibialis anterior muscle of 48 control subjects and 30 subjects with neuropathic disorders. These results demonstrate the possibility of detecting neuropathy using motor unit recruitment and mean firing rate feature values estimated from standard concentric needle detected EMG signals.
| Original language | English (US) |
|---|---|
| Title of host publication | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4066-4070 |
| Number of pages | 5 |
| ISBN (Print) | 9781424479290 |
| DOIs | |
| State | Published - Nov 2 2014 |
| Event | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: Aug 26 2014 → Aug 30 2014 |
Other
| Other | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
|---|---|
| Country | United States |
| City | Chicago |
| Period | 8/26/14 → 8/30/14 |
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ASJC Scopus subject areas
- Health Informatics
- Computer Science Applications
- Biomedical Engineering
Cite this
Detecting neuropathy using measures of motor unit activation extracted from standard concentric needle electromyographic signals. / Abdelmaseeh, Meena; Smith, Benn; Stashuk, Daniel.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 4066-4070 6944517.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Detecting neuropathy using measures of motor unit activation extracted from standard concentric needle electromyographic signals
AU - Abdelmaseeh, Meena
AU - Smith, Benn
AU - Stashuk, Daniel
PY - 2014/11/2
Y1 - 2014/11/2
N2 - Objective: Motor unit loss associated with neuropathic disorders affects motor unit activation. Quantitative electromyographic (EMG) features of motor unit activation estimated from the sequences of motor unit potentials (MUPs) created by concurrently active motor units can support the detection of neuropathic disorders. Interpretation of most motor unit activation feature values are, however, confounded by uncertainty regarding the level of muscle activation during EMG signal detection. A set of new features circumventing these limitations are proposed, and their utility in detecting neuropathy is investigated using simulated and clinical EMG signals. Methods: The firing sequence of a motor neuron was simulated using a compartmentalized Hodgkin-Huxley based model. A pool of motor neurons was modelled such that each motor neuron was subjected to a common level of activation. The detection of the firing sequence of a motor neuron using a clinically detected EMG signal was simulated using a model of muscle anatomy combined with a model representing muscle fiber electrophysiology and the voltage detection properties of a concentric needle electrode. Significance: Findings are based on simulated EMG data representing 30 normal and 30 neuropathic muscles as well as clinical EMG data collected from the tibialis anterior muscle of 48 control subjects and 30 subjects with neuropathic disorders. These results demonstrate the possibility of detecting neuropathy using motor unit recruitment and mean firing rate feature values estimated from standard concentric needle detected EMG signals.
AB - Objective: Motor unit loss associated with neuropathic disorders affects motor unit activation. Quantitative electromyographic (EMG) features of motor unit activation estimated from the sequences of motor unit potentials (MUPs) created by concurrently active motor units can support the detection of neuropathic disorders. Interpretation of most motor unit activation feature values are, however, confounded by uncertainty regarding the level of muscle activation during EMG signal detection. A set of new features circumventing these limitations are proposed, and their utility in detecting neuropathy is investigated using simulated and clinical EMG signals. Methods: The firing sequence of a motor neuron was simulated using a compartmentalized Hodgkin-Huxley based model. A pool of motor neurons was modelled such that each motor neuron was subjected to a common level of activation. The detection of the firing sequence of a motor neuron using a clinically detected EMG signal was simulated using a model of muscle anatomy combined with a model representing muscle fiber electrophysiology and the voltage detection properties of a concentric needle electrode. Significance: Findings are based on simulated EMG data representing 30 normal and 30 neuropathic muscles as well as clinical EMG data collected from the tibialis anterior muscle of 48 control subjects and 30 subjects with neuropathic disorders. These results demonstrate the possibility of detecting neuropathy using motor unit recruitment and mean firing rate feature values estimated from standard concentric needle detected EMG signals.
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U2 - 10.1109/EMBC.2014.6944517
DO - 10.1109/EMBC.2014.6944517
M3 - Conference contribution
SN - 9781424479290
SP - 4066
EP - 4070
BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -