1. Filtering Signal Processing.2
The EMG Signal
Filtering
Signal Processing.2

2. Filters - Overview Primary function is noise attenuation
If the frequency of the noise source is sufficiently different from the frequency components of the signal waveform of interest - the noise can be removed providing a “cleaner” EMG signal

3. Filters - Overview Frequency range of muscle - slow twitch motor units
(20) Hz

4. Filters - Overview Frequency range of muscle - slow twitch motor units
Fast twitch motor units Hz

5. Filters - Overview Frequency range of muscle - slow twitch motor units
Fast twitch motor units
Sources of noise that “compete” with these frequency ranges
Attenuate or make the true signal less visible and difficult to interpret
Example: 60 Hz from 120 V power lines

6. Filter Types Hardware filters Software filters
Analog electronic circuit
Amplifiers, resistors, capacitors
Software filters
“Digital” filters
Mathematical algorithms
Butterworth Filter.vi

7. Frequency Components Bandwidth Low frequency cut-off
Range of frequencies from the low frequency limit of the EMG signal to the high frequency limit = the band pass
Low frequency cut-off
High frequency cut-off
Roll off
Rate at which frequency attenuation occurs

8. Frequency Components

9. Filter Types by Frequency Component
High frequency filter
Removes high frequency components above a certain “cut-off”
Low pass filter (LP)
Pass = retain
20 Hz
250 Hz LP
Filter

10. Filter Types by Frequency Component
Low - High frequency filter
Removes frequency components below and above certain “cut-offs”
Band pass filter (BP)
20 Hz
250 Hz
Filter BP
Filter

11. Filter Types by Frequency Component
60 Hz
Mid-range frequency filter
Removes a specific frequency component within a range
Band stop filter (BS)
Example: 60 Hz filter
20 Hz
250 Hz BS

12. Roll Off Rate at which frequency attenuation occurs
Expressed by the order
The higher the order the more rapid the roll off
Index of sensitivity of attenuation
Butterworth Filter.vi

13. Phase Shift Filtering causes a change in phase = shift
A time delay frequency component as it passes through the filter
May cause waveform distortion especially if the the shift occurs near the cut-off frequency
If the phase shift is small it may be a tolerable error source
Shift

14. Phase Shift Solution

15. Filter Use
Turn filter “On”
Select type
Insert cut-off(s)
Run the VI

16. Practical Effect - Filtering
Filtering will “sharpen” the image permitting better approximation of important events
Onsets
Offsets
Etc.

17. Practical Effect - Filtering
Raw
Filtered

18. Signal Processing.2 Descriptive statistics Root Mean Square
Signal spike counts
Peak amplitude (voltage - mV) detection
Averaging
Variability analysis
Root Mean Square

19. Descriptive Statistics
Often used as a basic means of analysis after visual inspection of the raw data
Probably more useful in quantifying “On-Off” phenomena
May be used in conjunction with time-based analyses: onset, duration & offset

20. Signal Spike Counts
More useful when muscle force levels are relatively low
The interference pattern typical of high force levels (e.g., MVC) makes spike counts difficult

21. Signal Spike Counts Spike Counting by Window Spike Counting of Raw
Signal - (could also be done
with rectified signal)

22. Peak Amplitude
Has traditionally been issued as an index of maximal muscle activity
Probably valid when electrical activity is relatively constant
A peak amplitude that exists more as an outlier may not be truly representative of typical or average activity
Full-Wave Rectified Signal

23. Averaging (Mean)
A data smoothing technique useful when high signal variability is of concern
Moving average - the mean amplitude of a full-wave rectified window (segment) of data points for:
Baseline noise (last session: “2 SD Method”)
The true EMG signal
Ensemble average - a mean of mean segments across subjects or trials

24. Variability Analysis.1
Reproducibility of recording electrodes (e.g., Δ’s in skin resistance; number of motor units sampled) with repeated measures designs is problematic
Within subjects (e.g., over several days)
Between subjects
Report EMG amplitude (e.g., mean amplitude or integral - next session) as a percentage of a baseline MVIC

25. Variability Analysis.2
Variability assessment of EMG will document reproducibility/consistency
SD: measure of dispersion about the mean stated in units of interest (mV)
CV: describes dispersion of a group mean as a percentage
SE: low SE argues sample mean is a good estimate of the population mean

26. Root Mean Square (RMS)
One of several methods of quantifying EMG output (in mV) using
Hardware or
Software
The “effective” value (quantity) of the EMG signal (i.e., not an average)
Measures electrical power
A form of linear envelope procedure

27. RMS Value Reflects Motor unit Electrode configuration
Firing rates
Duration
Velocity of the electrical signal
Electrode configuration
Instrument (amplifier characteristics)

28. RMS Procedure Individual amplitudes are squared
A mean of the squared amplitudes is calculated
Square root is calculated

29. RMS - Time Constant Selected
Hardware

30. RMS - Time Constant Selected
Hardware
Software

31. RMS - Time Constant
Should be consistent with the nature of the activity being performed
Slow movement
Use a longer time
Fast movement
Use a shorter time

32. Reference Sources
Gitter, A.J., & Stolov, W.C. (1995). AAEM minimongraph #16: instrumentation and measurement in electrodiagnostic medicine-part I. Muscle & Nerve, 18,

33. Reference Sources
Soderberg, G.L., & Knutson, L.M, (2000). A guide for use and interpretation of kinesiologic electromyographic data. Physical Therapy, 80,
Winter, D.A. (1990). Biomechanics and motor control of human movement (2nd Ed). New York: John Wiley & Sons, Inc.,