DQEMG: Decomposition-based Quantitative EMG

1. Copyright Daniel W. Stashuk and Timothy J. Doherty, 2007. Some rights reserved. Content in this presentation is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License. This license is more fully described at: http://creativecommons.org/licenses/by-nc-sa/3.0/. DQEMG: Decomposition-based Quantitative EMG Daniel W. Stashuk, PhD University of Waterloo Timothy J. Doherty MD, PhD, FRCPC The University of Western Ontario

2. Objectives • Brief review of quantitative EMG • Principles of decomposition EMG • Basic overview of DQEMG • How can DQEMG be used for clinical and research applications • Validation and reliability of the method

5. Important Neuromuscular Information • Numbers of MUs • Relative sizes of MUs • Morphology of MUs • Recruitment of MUs • Firing patterns of MUs • Functional stability of neuromuscular junctions

6. Why Develop Quantitative EMG Methods? • Objectivity • Increased Sensitivity • Increased Specificity • Ability to determine degree of involvement • Improved ability provide longitudinal assessments

7. Quantitative EMG methods • Single Fiber EMG • Quantitative MUP analysis • Semi-automated MUP analysis • Automated MUP analysis • Interference pattern analysis • Motor unit number estimation

8. Quantitative EMG methods • Single Fiber EMG • Quantitative MUP analysis • Semi-automated MUP analysis • Automated MUP analysis • Interference pattern analysis • Motor unit number estimation

9. What is an EMG Signal? • MFP - muscle fibre potential • MUP - motor unit potential • MUPT - motor unit potential train • Composite EMG

10. EMG Signal Composition

11. MUPT - components of a MUPT

12. What is an Electromyographic (EMG) Signal?

13. Example Composite EMG Signal

14. Concepts of EMG Signal Decomposition

15. Basic Assumptions: How can an EMG Signal Be Decomposed? • Each MUP can be detected • Each detected MUP can be recognized Basic Requirements: • Common MUP feature is available for detection • MUPs within the same MUPT are more similar than MUPs from different MUPTs • Typical MUPs can be determined for each MUPT (i.e., MUPs must occur in isolation)

16. Steps in EMG Signal Decomposition • Signal Acquisition • Segmentation (Detecting MUPs) • Feature Extraction • Clustering of Detected MUPs • Supervised Classification of Detected MUPs • Discovering MUPT Temporal Relationships • Resolving Superimposed MUPs

17. Steps In Signal Decomposition

18. Steps In Signal Decomposition

19. Steps In Signal Decomposition

20. DQEMG • Performs multiple passes through an EMG signal to complete a partial decomposition • Detection pass • absolute or relative criteria • multiply and disparately detected MUPs • Clustering pass • STBC (shape and temporal based clustering) • Analyzes a selected portion of the signal (3 to 8 s long) • Multiple Supervised Classification Passes • Certainty-based classification • Analyzes complete signal • Robustly and actively uses firing pattern information • Temporal relationships pass • accounts formultiply (linked MUPTs)and disparately (exclusive MUPTs) detected MUPs • Superimposed MUPs are not resolved

21. DQEMG • Concentric or mono-polar needle and surface or “macro” EMG signals acquired • 30 - 60 sec isometric contractions • Mild to moderate intensity • Twenty or more MUs from 4 – 6 contractions

22. Acquiring EMG Signals • Apply surface electrode configuration as per standard motor study with active electrode over motor point. • Acquire maximal CMAP

23. Acquiring EMG Signals

24. Acquiring EMG Signals • Apply surface electrode configuration as per standard motor study with active electrode over motor point. • Acquire maximal CMAP • Perform MVC and calculate MVCRMS

25. Acquiring EMG Signals

26. Acquiring EMG Signals • Apply surface electrode configuration as per standard motor study with active electrode over motor point. • Acquire maximal CMAP • Perform MVC and calculate MVCRMS • Insert needle electrode and position for sufficient signal quality (signal quality monitor V/s or kV/s2). • Have subject isometrically contract to desired level of effort or signal intensity (%MVCRMS effort and pps intensity monitors)

27. Acquiring EMG Signals

28. Acquiring EMG Signals • Apply surface electrode configuration as per standard motor study with active electrode over motor point. • Acquire maximal CMAP • Perform MVC and calculate MVCRMS • Insert needle electrode and position for sufficient signal quality (signal quality monitor V/s or kV/s2). • Have subject isometrically contract to desired level of effort or signal intensity (%MVCRMS effort and pps intensity monitors) • Decompose needle acquired signal and calculate available SMUPs • Reposition needle and repeat during a subsequent contraction • Continue until sufficient number of SMUPs acquired (20 –35)

29. Acquiring EMG Signals

32. Quantitative MUP analysis • Buchthal method – 1950’s • Concentic needle MUPs collected one-by-one from minimally contracting muscle • Slow • ++ patient and operator interaction • Biased population of MUPs • Relatively limited information provided – only MUP parameters

33. Quantitative Needle EMG Morphological parameters - prototypical MUP of each MUPT • duration, number of phases, turns, Vpp, area, area/amplitude ratio

36. Spike-triggered Averaging

40. Motor Unit Number Estimation Size of M-potential Mean S-MUP Size = MUNE McComas et al. 1971

41. CMAP Mean S-MUP template MUNE

43. Measurement of MUP Stability

44. Jitter Measurement Jitter MCD: 17.9 mS Blocking: 0% Mean IPI: 219 mS

47. Methods ofacquiring sampleof S-MUPs Incremental Stimulation Statistical MPS STA

49. Quantitative Needle EMG

50. Decomposition-Based S-MUPs