def normalizedEMG(analysis, emgChannels,contexts, method="MeanMax", fromOtherAnalysis=None, mvcSettings=None):
"""
normalizedEMG : perform normalization of emg in amplitude
:param analysis [pyCGM2.Processing.analysis.Analysis]: pyCGM2 analysis instance
:param emgChannels [string list]: label of your emg channels
:param contexts [string list]: contexts associated with your emg channel
**optional**
:param method [str]: method of amplitude normalisation (choice MeanMax[default], MaxMax, MedianMax)
:param fromOtherAnalysis [pyCGM2.Processing.analysis.Analysis]: amplitude normalisation from another analysis instance
"""
i=0
for label in emgChannels:
envnf = emgFilters.EmgNormalisationProcessingFilter(analysis,label,contexts[i])
if fromOtherAnalysis is not None and mvcSettings is None:
LOGGER.logger.info("[pyCGM2] - %s normalized from another Analysis"%(label))
envnf.setThresholdFromOtherAnalysis(fromOtherAnalysis)
if mvcSettings is not None:
if label in mvcSettings.keys():
LOGGER.logger.info("[pyCGM2] - %s normalized from MVC"%(label))
envnf.setThresholdFromOtherAnalysis(mvcSettings[label])
else:
if fromOtherAnalysis is not None:
LOGGER.logger.info("[pyCGM2] - %s normalized from an external Analysis"%(label))
envnf.setThresholdFromOtherAnalysis(fromOtherAnalysis)
else:
LOGGER.logger.info("[pyCGM2] - %s normalized from current analysis"%(label))
if method != "MeanMax":
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
elif method != "MaxMax":
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MaxMax)
elif method != "MedianMax":
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MedianMax)
envnf.run()
i+=1
del envnf
def normalizedEMG(analysis,
emgChannels,
contexts,
method="MeanMax",
fromOtherAnalysis=None):
"""
normalizedEMG : perform normalization of emg in amplitude
:param analysis [pyCGM2.Processing.analysis.Analysis]: pyCGM2 analysis instance
:param emgChannels [string list]: label of your emg channels
:param contexts [string list]: contexts associated with your emg channel
**optional**
:param method [str]: method of amplitude normalisation (choice MeanMax[default], MaxMax, MedianMax)
:param fromOtherAnalysis [pyCGM2.Processing.analysis.Analysis]: amplitude normalisation from another analysis instance
"""
i = 0
for label in emgChannels:
envnf = emgFilters.EmgNormalisationProcessingFilter(
analysis, label, contexts[i])
if fromOtherAnalysis is not None:
envnf.setThresholdFromOtherAnalysis(fromOtherAnalysis)
if method is not "MeanMax":
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
elif method is not "MaxMax":
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MaxMax)
elif method is not "MedianMax":
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MedianMax)
envnf.run()
i += 1
del envnf
def test_envelopPlotSingleEmg(self):
# ----DATA-----
DATA_PATH = pyCGM2.TEST_DATA_PATH+"GaitData\\EMG\\Hånnibøl Lecter-nerve block\\"
gaitTrial = "PRE-gait trial 01.c3d"
restTrial = "PRE-repos.c3d"
DATA_PATH_OUT = pyCGM2.TEST_DATA_PATH_OUT+"GaitData\\EMG\\Hånnibøl Lecter-nerve block\\"
files.createDir(DATA_PATH_OUT)
EMG_LABELS=['EMG1','EMG2']
acq = btkTools.smartReader(DATA_PATH +gaitTrial)
bf = emgFilters.BasicEmgProcessingFilter(acq,EMG_LABELS)
bf.setHighPassFrequencies(20.0,200.0)
bf.run()
envf = emgFilters.EmgEnvelopProcessingFilter(acq,EMG_LABELS)
envf.setCutoffFrequency(180.0)
envf.run()
btkTools.smartWriter(acq,DATA_PATH_OUT+"test_envelopPlotSingleEmg.c3d")
modelledFilenames = ["test_envelopPlotSingleEmg.c3d"]
c3dmanagerProcedure = c3dManager.UniqueC3dSetProcedure(DATA_PATH_OUT,modelledFilenames)
cmf = c3dManager.C3dManagerFilter(c3dmanagerProcedure)
cmf.enableSpatioTemporal(False)
cmf.enableKinematic(False)
cmf.enableKinetic(False)
cmf.enableEmg(True)
trialManager = cmf.generate()
#---- GAIT CYCLES FILTER
#--------------------------------------------------------------------------
cycleBuilder = cycle.GaitCyclesBuilder(spatioTemporalTrials=trialManager.spatioTemporal["Trials"],
kinematicTrials = trialManager.kinematic["Trials"],
kineticTrials = trialManager.kinetic["Trials"],
emgTrials=trialManager.emg["Trials"])
cyclefilter = cycle.CyclesFilter()
cyclefilter.setBuilder(cycleBuilder)
cycles = cyclefilter.build()
modelInfo=None
subjectInfo=None
experimentalInfo=None
analysisBuilder = analysis.GaitAnalysisBuilder(cycles,
kinematicLabelsDict = None,
kineticLabelsDict = None,
emgLabelList = ['EMG1_Rectify_Env','EMG2_Rectify_Env'],
subjectInfos=subjectInfo,
modelInfos=modelInfo,
experimentalInfos=experimentalInfo)
analysisFilter = analysis.AnalysisFilter()
analysisFilter.setBuilder(analysisBuilder)
analysisFilter.setInfo(model = modelInfo)
analysisFilter.build()
analysisInstance = analysisFilter.analysis
envnf = emgFilters.EmgNormalisationProcessingFilter(analysisInstance,"EMG1","Left")
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
envnf.run()
fig = plt.figure()
ax = plt.gca()
plot.gaitDescriptivePlot(ax,analysisInstance.emgStats,
"EMG1_Rectify_Env","Left",0,
color=None,
title="title", xlabel=None, ylabel=None,ylim=None,legendLabel=None,
customLimits=None)
footOff = analysisInstance.emgStats.pst['stancePhase', "Left"]["mean"]
plot.addNormalActivationLayer(ax,"RECFEM", footOff)
def test_envelopGaitPlotPanel(self):
# ----DATA-----
DATA_PATH = pyCGM2.TEST_DATA_PATH+"GaitData\\EMG\\Hånnibøl Lecter-nerve block\\"
gaitTrial = "PRE-gait trial 01.c3d"
restTrial = "PRE-repos.c3d"
DATA_PATH_OUT = pyCGM2.TEST_DATA_PATH_OUT+"GaitData\\EMG\\Hånnibøl Lecter-nerve block\\"
files.createDir(DATA_PATH_OUT)
EMG_LABELS=['EMG1','EMG2']
acq = btkTools.smartReader(DATA_PATH +gaitTrial)
bf = emgFilters.BasicEmgProcessingFilter(acq,EMG_LABELS)
bf.setHighPassFrequencies(20.0,200.0)
bf.run()
envf = emgFilters.EmgEnvelopProcessingFilter(acq,EMG_LABELS)
envf.setCutoffFrequency(180.0)
envf.run()
btkTools.smartWriter(acq,DATA_PATH_OUT+"test_envelopGaitPlotPanel.c3d")
modelledFilenames = ["test_envelopGaitPlotPanel.c3d"]
c3dmanagerProcedure = c3dManager.UniqueC3dSetProcedure(DATA_PATH_OUT,modelledFilenames)
cmf = c3dManager.C3dManagerFilter(c3dmanagerProcedure)
cmf.enableSpatioTemporal(False)
cmf.enableKinematic(False)
cmf.enableKinetic(False)
cmf.enableEmg(True)
trialManager = cmf.generate()
#---- GAIT CYCLES FILTER
#--------------------------------------------------------------------------
cycleBuilder = cycle.GaitCyclesBuilder(spatioTemporalTrials=trialManager.spatioTemporal["Trials"],
kinematicTrials = trialManager.kinematic["Trials"],
kineticTrials = trialManager.kinetic["Trials"],
emgTrials=trialManager.emg["Trials"])
cyclefilter = cycle.CyclesFilter()
cyclefilter.setBuilder(cycleBuilder)
cycles = cyclefilter.build()
modelInfo=None
subjectInfo=None
experimentalInfo=None
analysisBuilder = analysis.GaitAnalysisBuilder(cycles,
kinematicLabelsDict = None,
kineticLabelsDict = None,
emgLabelList = ['EMG1_Rectify_Env','EMG2_Rectify_Env'],
subjectInfos=subjectInfo,
modelInfos=modelInfo,
experimentalInfos=experimentalInfo)
analysisFilter = analysis.AnalysisFilter()
analysisFilter.setBuilder(analysisBuilder)
analysisFilter.setInfo(model = modelInfo)
analysisFilter.build()
analysisInstance = analysisFilter.analysis
envnf = emgFilters.EmgNormalisationProcessingFilter(analysisInstance,"EMG1","Right")
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
envnf.run()
envnf = emgFilters.EmgNormalisationProcessingFilter(analysisInstance,"EMG2","Right")
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
envnf.run()
data = analysisInstance.emgStats.data
# viewer
kv = emgPlotViewers.EnvEmgGaitPlotPanelViewer (analysisInstance)
kv.setEmgs([["EMG1","Right","rf"],["EMG2","Right","rf"]])
kv.setNormalActivationLabels(["RECFEM","RECFEM"])
kv.setConcretePlotFunction(plot.gaitDescriptivePlot)
# # filter
pf = plotFilters.PlottingFilter()
pf.setViewer(kv)
pf.plot()
def EnvelopCoactivationPlot(cls):
# ----DATA-----
DATA_PATH = pyCGM2.TEST_DATA_PATH + "EMG\\SampleNantes\\"
gaitTrial = "gait.c3d"
restTrial = "repos.c3d"
EMG_LABELS = ['EMG1', 'EMG2']
acq = btkTools.smartReader(DATA_PATH + gaitTrial)
bf = emgFilters.BasicEmgProcessingFilter(acq, EMG_LABELS)
bf.setHighPassFrequencies(20.0, 200.0)
bf.run()
envf = emgFilters.EmgEnvelopProcessingFilter(acq, EMG_LABELS)
envf.setCutoffFrequency(180.0)
envf.run()
btkTools.smartWriter(acq, DATA_PATH + "test.c3d")
modelledFilenames = ["test.c3d"]
c3dmanagerProcedure = c3dManager.UniqueC3dSetProcedure(
DATA_PATH, modelledFilenames)
cmf = c3dManager.C3dManagerFilter(c3dmanagerProcedure)
cmf.enableSpatioTemporal(False)
cmf.enableKinematic(False)
cmf.enableKinetic(False)
cmf.enableEmg(True)
trialManager = cmf.generate()
#---- GAIT CYCLES FILTER
#--------------------------------------------------------------------------
cycleBuilder = cycle.GaitCyclesBuilder(
spatioTemporalTrials=trialManager.spatioTemporal["Trials"],
kinematicTrials=trialManager.kinematic["Trials"],
kineticTrials=trialManager.kinetic["Trials"],
emgTrials=trialManager.emg["Trials"])
cyclefilter = cycle.CyclesFilter()
cyclefilter.setBuilder(cycleBuilder)
cycles = cyclefilter.build()
modelInfo = None
subjectInfo = None
experimentalInfo = None
analysisBuilder = analysis.GaitAnalysisBuilder(
cycles,
kinematicLabelsDict=None,
kineticLabelsDict=None,
emgLabelList=['EMG1_Rectify_Env', 'EMG2_Rectify_Env'],
subjectInfos=subjectInfo,
modelInfos=modelInfo,
experimentalInfos=experimentalInfo)
analysisFilter = analysis.AnalysisFilter()
analysisFilter.setBuilder(analysisBuilder)
analysisFilter.setInfo(model=modelInfo)
analysisFilter.build()
analysisInstance = analysisFilter.analysis
envnf = emgFilters.EmgNormalisationProcessingFilter(
analysisInstance, "EMG1", "Left")
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
envnf.run()
envnf = emgFilters.EmgNormalisationProcessingFilter(
analysisInstance, "EMG2", "Left")
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
envnf.run()
# viewer
kv = emgPlotViewers.CoactivationEmgPlotViewer(analysisInstance)
kv.setEmgs("EMG1", "EMG2")
kv.setMuscles("RF1", "RF2")
kv.setConcretePlotFunction(plot.gaitDescriptivePlot)
kv.setContext("Left")
# # filter
pf = plotFilters.PlottingFilter()
pf.setViewer(kv)
pf.plot()
plt.show()
def NormalizationTest(cls):
# ----DATA-----
DATA_PATH = pyCGM2.TEST_DATA_PATH+"EMG\\SampleNantes\\"
gaitTrial = "gait.c3d"
restTrial = "repos.c3d"
EMG_LABELS=['EMG1','EMG2']
acq = btkTools.smartReader(DATA_PATH +gaitTrial)
bf = emgFilters.BasicEmgProcessingFilter(acq,EMG_LABELS)
bf.setHighPassFrequencies(20.0,200.0)
bf.run()
envf = emgFilters.EmgEnvelopProcessingFilter(acq,EMG_LABELS)
envf.setCutoffFrequency(180.0)
envf.run()
btkTools.smartWriter(acq,DATA_PATH+"test.c3d")
modelledFilenames = ["test.c3d"]
c3dmanagerProcedure = c3dManager.UniqueC3dSetProcedure(DATA_PATH,modelledFilenames)
cmf = c3dManager.C3dManagerFilter(c3dmanagerProcedure)
cmf.enableSpatioTemporal(False)
cmf.enableKinematic(False)
cmf.enableKinetic(False)
cmf.enableEmg(True)
trialManager = cmf.generate()
#---- GAIT CYCLES FILTER
#--------------------------------------------------------------------------
cycleBuilder = cycle.GaitCyclesBuilder(spatioTemporalTrials=trialManager.spatioTemporal["Trials"],
kinematicTrials = trialManager.kinematic["Trials"],
kineticTrials = trialManager.kinetic["Trials"],
emgTrials=trialManager.emg["Trials"])
cyclefilter = cycle.CyclesFilter()
cyclefilter.setBuilder(cycleBuilder)
cycles = cyclefilter.build()
modelInfo=None
subjectInfo=None
experimentalInfo=None
analysisBuilder = analysis.GaitAnalysisBuilder(cycles,
kinematicLabelsDict = None,
kineticLabelsDict = None,
emgLabelList = ['EMG1_Rectify_Env','EMG2_Rectify_Env'],
subjectInfos=subjectInfo,
modelInfos=modelInfo,
experimentalInfos=experimentalInfo)
analysisFilter = analysis.AnalysisFilter()
analysisFilter.setBuilder(analysisBuilder)
analysisFilter.setInfo(model = modelInfo)
analysisFilter.build()
analysisInstance = analysisFilter.analysis
envnf = emgFilters.EmgNormalisationProcessingFilter(analysisInstance,"EMG1","Left")
envnf.setMaxMethod(enums.EmgAmplitudeNormalization.MeanMax)
envnf.run()
envnf.processC3d([DATA_PATH+"test.c3d"], fileSuffix="test")
print analysisInstance.emgStats.data.keys()
