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The EMG Signal Filtering Signal Processing.2

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Filters - Overview u Primary function is noise attenuation u 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

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

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

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Filters - Overview u Frequency range of muscle - slow twitch motor units u Fast twitch motor units u Sources of noise that “compete” with these frequency ranges u 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 u Hardware filters –Analog electronic circuit »Amplifiers, resistors, capacitors u Software filters –“Digital” filters »Mathematical algorithms Butterworth Filter.vi

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

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Frequency Components

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

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

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

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

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Phase Shift u 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 u If the phase shift is small it may be a tolerable error source Shift

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Phase Shift Solution

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

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

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Practical Effect - Filtering Raw Filtered

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

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Descriptive Statistics u 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 u More useful when muscle force levels are relatively low –The interference pattern typical of high force levels (e.g., MVC) makes spike counts difficult

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

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Peak Amplitude u 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) u A data smoothing technique useful when high signal variability is of concern u 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 u Ensemble average - a mean of mean segments across subjects or trials

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Variability Analysis.1 u 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 u 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 u 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) u One of several methods of quantifying EMG output (in mV) using –Hardware or –Software u The “effective” value (quantity) of the EMG signal (i.e., not an average) u Measures electrical power u A form of linear envelope procedure

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

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

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RMS - Time Constant Selected u Hardware

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RMS - Time Constant Selected u Hardware u Software

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RMS - Time Constant u 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,

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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, Winter, D.A. (1990). Biomechanics and motor control of human movement (2nd Ed). New York: John Wiley & Sons, Inc.,

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