Analog Data Processing with BioProc3

Analog Data Processing withBioProc3 Part Two EMG Analysis Techniques

Bias Removal • high-pass filtering with a Butterworth filter is usually best • use Autozero, Drift and Autozero orMean from Bias Removal menu • for an AC signal, using the means can be effective • once the biases have been determined they can be saved for later use • autozeroing is used for piezoelectric signals such as signals from Kistler force platforms or accelerometers Gait & Biomechanics Laboratory, School of Human Kinetics

Notch Filtering of Line Frequency • use a Buttterworth band-stop filter from the Digital Filtering (various) item in the Smoothing menu • set the low-pass frequency to 59.5 Hz and the high-pass frequency to 60.5 Hz • note that any 60 Hz EMG data will also be removed Gait & Biomechanics Laboratory, School of Human Kinetics

MAV – 0.1 s RMS – 0.1 s Linear Envelope, RMS or MAV • root-mean-square (RMS) and mean-absolute-values (MAV) are in the data smoothing menu • linear-envelope detection rectifies (absolute values) the signal and then passes the data through a low-pass filter (usually not zero-lag) raw EMG LE fc=5 Hz Gait & Biomechanics Laboratory, School of Human Kinetics

Integration • definite integration (scalar) can be done within the graphics mode by pressing “I” or “E” or selecting Statistics | All data or Between Cursors and then Integration stats. or EMG stats. • use the value under the column labeled Abs. Integ’l • integration by epoch allows for repetitive definite integrals for selected durations called epochs • this option is selected from the EMG Analysis item in the Analysis menu • a graph of the results is presented and may be stored • use the absolute integral or RMS results • results may be sent to Notepad, Quattro Pro or Excel • use Integrate and Reset item to integrate over set time intervals • use Rectify and Integrate for an indefinite integral Gait & Biomechanics Laboratory, School of Human Kinetics

EMG Onset Detection • first use a Butterworth high-pass filter to remove any drift or bias or movement artifacts (5–10 Hz cutoff) • next use a critically-damped low-pass filter with the checkbox Rectify signal(s) for Linear Envel. checked (< 5 Hz) • graph the data in multiaxis mode, one curve per graph • press 2 to get cursors then select an area of resting EMGs • press Threshold then Calculate Thresholds • click on a curve to change a threshold then press “T” to set it • move cursors to an area then press Onsets from the Cursor menu Gait & Biomechanics Laboratory, School of Human Kinetics

Event Tracking • press F9 to start event tracking then double-click each curve or right-click to record events for all waveforms • press Insert button to create a second set of events • press Delete button to delete the last set of events • press F10 to save the events in a file (.bpv) • the file will record the times of both the left and right cursors and each waveforms’ associated amplitudes • the file can be viewed in a spreadsheet or test editor (Notepad) Gait & Biomechanics Laboratory, School of Human Kinetics

Fourier Analysis • use Harmonic Regression or Fast Fourier Transform from the Fourier Analysis menu • FFT usually requires a windowing technique (e.g., Hamming, Blackwood, Cosine Tapered, etc. Rectangular means no windowing). Select the windowing technique, then press the Power Spectrum (FFT) option • Harmonic Regression is slower but has more features and fewer restrictions than an FFT • check which channels to analyze and enter the maximum number of harmonics to be computed • results may be graphed or tabulated and saved for later use including signal reconstruction (.FTF format) Gait & Biomechanics Laboratory, School of Human Kinetics

Fatigue Analysis • fatigue analysis is a series of sequential Fourier analyses • press Fatigue Analysis from the EMG Analysis menu • select FFT or Harmonic Regression (FFT is faster) • if FFT select window width as a power of 2 • if Harmonic Analysis select duration and maximum number of harmonics • you can interleave the data to create greater resolution • press Select Channel to process one channel at a time • table will appear of the results • press Graph button to view data two dimensionally • use checkboxes to select which data are displayed graphically • press 3D to view a three-dimensional graph Gait & Biomechanics Laboratory, School of Human Kinetics

Ensemble or EMG Signal Averaging • this is a powerful tool for averaging a series of cyclical data • for EMG data signals must first be rectified by using moving RMS or MAV averaging or using a linear-envelope detector • the software will average multiple waveforms, simultaneously, for example a group of EMG signals from the same person • it can average multiple trials of the same person or average across a group of subjects • select Ensemble Averaging from the Analysis menu • data should be cropped so that each cycle is in a single file • (new) cycles can be selected graphically and saved • use high and low pass filtering as necessary • amplitude normalize as needed Gait & Biomechanics Laboratory, School of Human Kinetics

Steps for Ensemble Averaging • enter a filename to hold the results • select a “mask” that can be used to create the filenames of the input data • enter the number of intervals for the time-base normalization usually 100 is used to get “cycle percentage” • select the first file to be averaged this step determines the number of channels that will be averaged • button 5 allows you to change your channel selection • press button 6 to start the averaging process • use button 7 to add other files and use 8 to remove the last file • press the Graph Last File button to view files as they are added • press button 9 to compute the ensemble average and SDs Gait & Biomechanics Laboratory, School of Human Kinetics

Results from Ensemble Averaging • list at right shows the filenames that have been added or removed and the actual time durations of each file • coefficients of variation for each channel are calculated • press Graph Results to view the means and standard deviations for each channel. The data are paired in multiaxis graphs. Dashed lines are the SDs. • press button 10 to save the ensemble averages in .BPB (BioProc2 Binary) format • press Export to Excel or Quattro to view the data in spreadsheet format • to change from Excel to Quattro Pro use the Options menu from the main screen Gait & Biomechanics Laboratory, School of Human Kinetics

Analog Data Processing with BioProc3