Transcript BioProc2 - University of Ottawa

Analog Data
Processing with
BioProc3
Part Two
EMG Analysis Techniques
Bias Removal
• high-pass filtering with a Butterworth filter is usually best
• use Autozero, Drift and Autozero or Mean 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
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
MAV – 0.1 s
RMS – 0.1 s
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
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
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
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
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
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
1. enter a filename to hold the results
2. select a “mask” that can be used to create the filenames of the
input data
3. enter the number of intervals for the time-base normalization
usually 100 is used to get “cycle percentage”
4. select the first file to be averaged this step determines the
number of channels that will be averaged
5. button 5 allows you to change your channel selection
6. press button 6 to start the averaging process
7. use button 7 to add other files and use 8 to remove the last file
8. press the Graph Last File button to view files as they are added
9. press button 9 to compute the ensemble average and SDs
Gait & Biomechanics Laboratory, School of Human Kinetics
Steps for Ensemble Averaging
1. enter a filename to hold the results
2. select a “mask” that can be used to create the filenames of the
input data
3. enter the number of intervals for the time-base normalization
usually 100 is used to get “cycle percentage”
4. select the first file to be averaged this step determines the
number of channels that will be averaged
5. button 5 allows you to change your channel selection
6. press button 6 to start the averaging process
7. use button 7 to add other files and use 8 to remove the last file
8. press the Graph Last File button to view files as they are added
9. press button 9 to compute the ensemble average and SDs
Gait & Biomechanics Laboratory, School of Human Kinetics
Steps for Ensemble Averaging
1. enter a filename to hold the results
2. select a “mask” that can be used to create the filenames of the
input data
3. enter the number of intervals for the time-base normalization
usually 100 is used to get “cycle percentage”
4. select the first file to be averaged this step determines the
number of channels that will be averaged
5. button 5 allows you to change your channel selection
6. press button 6 to start the averaging process
7. use button 7 to add other files and use 8 to remove the last file
8. press the Graph Last File button to view files as they are added
9. 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
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