The EMG Signal

1
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) 70 - 125 Hz

4
Filters - Overview

• Frequency range of muscle - slow twitch motor
  units
• Fast twitch motor units

• 125 - 250 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

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Filter Types

• Hardware filters
• Analog electronic circuit
• Amplifiers, resistors, capacitors
• Software filters
• Digital filters
• Mathematical algorithms

Butterworth Filter.vi
7
Frequency Components

• Bandwidth
• 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

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Frequency Components
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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
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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
BP
Filter
Filter
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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
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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
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Filter Use

• Turn filter On
• Select type
• Insert cut-off(s)
• Run the VI

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Practical Effect - Filtering

• Filtering will sharpen the image permitting
  better approximation of important events
• Onsets
• Offsets
• Etc.

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Practical Effect - Filtering
Raw
Filtered
18
Signal Processing.2

• Descriptive statistics
• 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

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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
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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

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Variability Analysis.1

• Reproducibility of recording electrodes (e.g.,
  ?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

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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

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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

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RMS Value Reflects

• Motor unit
• Firing rates
• Duration
• Velocity of the electrical signal
• Electrode configuration
• Instrument (amplifier characteristics)

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RMS Procedure

• Individual amplitudes are squared
• A mean of the squared amplitudes is calculated
• Square root is calculated

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RMS - Time Constant Selected

• Hardware

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RMS - Time Constant Selected

• Hardware
• Software

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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

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Reference Sources

• Gitter, A.J., Stolov, W.C. (1995). AAEM
  minimongraph 16 instrumentation and measurement
  in electrodiagnostic medicine-part I. Muscle
  Nerve, 18, 799-811.

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Reference Sources

• Soderberg, G.L., Knutson, L.M, (2000). A guide
  for use and interpretation of kinesiologic
  electromyographic data. Physical Therapy, 80,
  485-498.
• Winter, D.A. (1990). Biomechanics and motor
  control of human movement (2nd Ed). New York
  John Wiley Sons, Inc., 191-212.

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