Electromyography: Processing

1. Electromyography: Processing D. Gordon E. Robertson, PhD Biomechanics Laboratory, School of Human Kinetics, University of Ottawa, Ottawa, CANADA

2. Types of Signal Processing • Raw (with or without band-pass filtering) • Full-wave rectified (absolute value) • Averaged or root-mean-square (RMS) • Linear envelope • Ensemble-averaged • Integrated • Frequency or power spectrum (Fourier) • Fatigue analysis (sequential Fourier) • Amplitude probability distribution function (APDF) and CAPDF

3. Raw EMG • wide frequency spectrum (20-500 Hz) • most complete information • needs 1000 Hz or greater sampling rates • requires large memory storage • difficult to determine “levels” of contraction • bursts of activity and “onset times” may be determined from this signal • best for examining problems with recording • following slides show some errors that can be detected from the raw signal

4. heart rate detected Errors when Recording EMGs -1 • “clean” signal • with ECG crosstalk

5. ECG Crosstalk • ECG crosstalk occurs when recording near the heart (ECG has higher voltages then EMG) • EEG crosstalk when near scalp (rare) • difficult to resolve • use right side of body (away from heart) • move electrodes as far away from heart as possible • “signal averaging” (average many trials) • indwelling electrodes

6. Muscle Crosstalk • one muscle’s EMG is picked up by another muscle’s electrodes • can be reduced by careful electrode positioning • can be determined by cross-correlation • difficult to distinguish crosstalk from synergistic contractions • biarticular muscles have “extra” bursts of activity compared to monoarticular muscles (if so crosstalk is not a problem)

7. 60 Hz noise baseline not at zero volts Errors when Recording EMGs -2 • with line (AC) interference • with DC-offset or DC-bias

8. Solutions • To interference (of line and radio freq. etc.) • Keep away from fluorescent lighting • Keep away from large electrical devices and power cords (especially leads and cabling) • Use room lined with grounded conductive material • Keep leads short and braided (vs. radio) • Use preamplified electrodes (signal is stronger) • Use extremely narrow notch filter in post processing (e.g., 59.5-60.5 Hz) • For DC-offsets • Telemetry systems often have DC-offsets • Use a good ground electrode over electrically neutral area • Use high-pass filter to remove in post-processing

9. electrodes were struck clipped at +/–0.5 V Errors when Recording EMGs -3 • with movement artifact • with amplifier saturation (+/–0.5 V)

10. Solutions • To movement artifacts • Affix leads to subject (tape or wraps) • Prevent electrodes from being struck (use lateral muscles) • Avoid rapid motions • Use strong high-pass filter in post-processing • Amplifier saturation • Test with maximal contractions before recording • Reduce gain if peaks and valleys, “top” or “bottom” out • Use larger range of A/D converter (+/–10 V)

11. Full-wave Rectified EMG • same as taking the absolute value of the raw signal • mainly used as an intermediate step before another process (e.g., averaging, linear envelope and integration) • can be done electronically and in real-time

12. Sample EMGs • raw EMG (band-passed filtered, 20-500 Hz) • full-wave rectified

13. Averaged EMG • simple to compute • can be done in real-time • averaged EMG is a “moving average” of a full-wave rectified EMG • must select an appropriate “window width”that changes with sampling rate • easy for determining levels of contraction

14. Sample Averaged EMG • raw EMG (1010 Hz sampling rate) • averaged EMG (moving average, 51 points)

15. Linear Envelope EMG • requires two-step process: full-wave rectification followed by low-pass filter (4-10 Hz cutoff) • can be done electronically (but adds a delay) • reduces frequency content of EMG and thus lowers sampling rates (e.g., 100 Hz) and memory storage • easy to interpret and to detect onset of activity • can be ensemble-averaged to obtain patterns • difficult to detect artifacts • useful as a control (myoelectric) signal

16. can have a time lag Sample LE-EMG • raw (band-passed filtered) EMG • linear envelope EMG (cutoff 4 Hz)

17. Ensemble-Averaged EMG • usually applied to cyclic activities and linear envelope EMGs • requires means for identifying start of cycle or start and end of activity • foot switches or force platforms can be used for gait studies • microswitches, optoelectric or electromagnetic sensors for other activities • can also use a threshold detector of a kinematic or EMG channel • each “cycle” of activity must be time normalized

18. Ensemble-Averaged EMG cont’d • amplitude normalization is often done • to maximal voluntary contraction (MVC) • to submaximal isometric contraction • to EMG of a functional activity • mean and standard deviations for each proportion of cycle are computed • mean and s.d. or 95% confidence interval may be presented to show representative contraction during activity cycle • easier to make comparisons among subjects • “grand” ensemble-averages (average of averages) for comparisons among several experimental conditions

19. mean +/–S.D. abscissa must be normalized to % cycle ordinate may also be normalized Ensemble-Averages from Squat Lift

20. Integrated EMG (iEMG) • important for quantitative EMG relationships (EMG vs. force, EMG vs. work) • best measure of the total muscular effort • useful for quantifying activity for ergonomic research • various methods: • mathematical integration (area under absolute values of EMG time series) • root-mean-square (RMS) times duration is similar but does not require taking absolute values • electronically (see next page)

21. Electronically Integrated EMG • always requires full-wave rectification • various methods: • simple time integration (eventually saturates amplifier) • integration and reset after a fixed time interval • integration and reset after a particular value is reached • cannot recognize artifacts, noise will be included • especially important to remove DC-offsets • must compute amount of iEMG from amplitude or differences between 2 amplitudes

22. notice units are mV.s read total iEMG from curve (i.e., 320 mV.s) Sample Integrated EMG • raw (band-passed filtered) EMG • integrated EMG (over contraction)

23. add each peak to get total IEMG notice units are mV.s multiply number of peaks by 20 mV.s Other iEMGs • integrate after preset time (0.1 s) • integrate after preset voltage (20 mV.s)

24. Frequency Spectrum • useful for determining onset of muscle fatigue • mean or median frequency of spectrum in unfatigued muscle is usually between 50-80 Hz • as fatigue progresses fast-twitch fibres drop out, shifting frequency spectrum to left (lowering mean and median frequencies) • mean frequency is less variable and therefore is better than median • useful for detecting neural abnormalities

25. gradual increase to >95% after 200 Hz median frequency approx. 70 Hz Sample Power Spectrum • flexor digitorum longus (MVC)

26. Fatigue Analysis • essentially a series of frequency analyses • select duration of window (1 to 5 s) • can overlap intervals to increase resolution • usually normalized to percentage of initial mean or median frequency • mean frequencies are less variable than median • need to decide a threshold for when fatigue occurs (i.e., fatigue has occurred when mean or median frequency is below a threshold)

27. gradual decline of mean and median frequencies medians are more variable Sample Fatigue Analysis • erector spinae over 60 seconds (50% overlap)

28. Amplitude Probability Distribution Function (APDF & CAPDF) • developed by Hagberg & Jonsson for ergonomics research (Ergonomics, 18:311-319) • EMG is amplitude normalized to %MVC then sampled to compute frequencies of various amplitudes, usually for long durations (hours) • Cumulative APDF is calculated to compute three thresholds: • 10%tile < 2–5% MVC for level of rest • 50%tile < 10–14% MVC for work load • 90%tile < 50–70% MVC for heavy contractions

29. 90%tile =52%MVC 50%tile =8%MVC 10%tile =2%MVC Sample APDF & CAPDF • neck flexor (only 5 minutes)

30. Other Techniques • auto-correlation (correlate signal with itself shifted in time, gives signal characteristics) • cross-correlation (correlate signal with another EMG signal, tests for crosstalk) • zero-crossings (the more crossings the greater the level of recruitment) • peak counting (number of peaks above a threshold) • single motor unit detection • double differential amplifier (velocity of propagation)