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Muscle innervation zone estimation from monopolar high-density M-waves using principal component analysis and radon
Chengjun Huang1, Zhiyuan Lu2, Maoqi Chen2
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States.
Frontiers in Physiology
|April 3, 2023
Summary
Principal component analysis (PCA) accurately estimates muscle innervation zones (IZ) using monopolar M waves. This automated method offers a valuable alternative for detecting muscle activation, especially in patients with impaired voluntary movement.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Electrophysiology
Background:
- Accurate estimation of the muscle innervation zone (IZ) is crucial for understanding muscle function and developing targeted interventions.
- Current methods for IZ detection can be labor-intensive and may not be suitable for all patient populations.
Purpose of the Study:
- To evaluate the efficacy of principal component analysis (PCA) and Radon transform (RT) for estimating muscle innervation zones (IZ) using high-density surface electromyography (HD-sEMG) monopolar M waves.
- To compare the performance of PCA and RT based methods against manual IZ detection and cross-correlation analysis.
Main Methods:
- High-density M waves were recorded from the biceps brachii muscles of nine healthy subjects using monopolar electrode configurations.
- Two automated methods, PCA and RT, were applied to estimate the IZ.
- The accuracy of the automated methods was assessed by comparing their results to manual IZ identification by experienced operators and to cross-correlation analysis using bipolar recordings.
Main Results:
- The PCA-based method achieved an 83% agreement rate with manual IZ detection, outperforming the RT-based method (63%) and cross-correlation analysis (56%).
- PCA demonstrated a lower mean difference in IZ location (0.12 ± 0.28 inter-electrode-distance) compared to RT (0.33 ± 0.41 IED) and cross-correlation (0.39 ± 0.74 IED).
- Monopolar HD-sEMG recordings combined with PCA provided reliable IZ estimation.
Conclusions:
- Principal component analysis (PCA) is a robust and accurate method for automatically estimating muscle innervation zones (IZ) from monopolar high-density M waves.
- PCA presents a valuable alternative to existing methods for IZ detection, particularly in clinical settings involving voluntary or electrically-evoked muscle contractions.
- This technique holds significant promise for IZ detection in patients experiencing impaired voluntary muscle activation.
