Assessment of validity of a high-yield surface electromyogram decomposition.
BACKGROUND
Using recordings from a five-pin surface sensor array, a template-based surface electromyogram (sEMG) decomposition system has been developed to identify single motor unit discharge properties. However, the reliability of such template based decomposition results has not been thoroughly examined except by the developers. The focus of this study was to assess the validity of the motor unit decomposition technique, using EMG recordings from the first dorsal interosseous muscle of able-bodied human subjects.


METHODS
Two tests were utilized. In the first test, a spike triggered averaging (STA) analysis was used to derive motor unit action potential (MUAP) parameters. We examined these STA derived MUAP shapes after firing times were perturbed by added timing noise. In the second test, a cross-correlation analysis was performed between the sEMG signal and MUAP trains constructed using STA estimates and their firing times.


RESULTS
In the first test, we found that MUAP shape features deteriorated significantly when rather small (0.6-2 ms) timing errors were added, affirming that the decomposed firing times are presumptively valid. The results of the second test reveal that the cross-correlation index between the EMG and MUAP trains increased monotonically up to 0.71 when the identified MUs were progressively added to reconstructed MUAP trains; however, this increment disappeared when the firing times or the MUAP templates were shifted randomly.


CONCLUSIONS
Based on our STA selection criteria, our results suggest that the firing times and estimated MUAP shapes for each MU generated by the decomposition algorithms are presumptively valid.
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, 345 E Superior Street, Room 1378, Chicago, IL 60611, USA. xiaogang.hu@northwestern.edu.
Xiaogang
X
Hu
William Z
WZ
Rymer
Nina L
NL
Suresh
D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D004576:Electromyography; D005260:Female; D006801:Humans; D008297:Male; D009046:Motor Neurons / Q000502:physiology; D018482:Muscle, Skeletal / Q000502:physiology; D012815:Signal Processing, Computer-Assisted