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

Filters - Overview Frequency range of muscle - slow twitch motor units (20) 70 - 125 Hz

Filters - Overview Frequency range of muscle - slow twitch motor units Fast twitch motor units 125 - 250 Hz

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

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

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

Frequency Components

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

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

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

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

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

Phase Shift Solution

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

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

Practical Effect - Filtering Raw Filtered

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

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

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

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

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

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

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

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

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

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

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

RMS - Time Constant Selected Hardware

RMS - Time Constant Selected Hardware Software

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

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.

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.