def feature_extraction_live(w_emg, w_imu, feature_set=Constant.rehman):
"""
Extracts the features of a given feature-set from the given raw data
:param w_emg:matrix
The matrix of the windowed raw data for the EMG signals
:param w_imu:matrix
The matrix of the windowed raw data for the IMU signals
:param feature_set:string
From this feature-set the features are extracted for extraction
:return:matrix
Matrix of extracted features. By default the features for EMG and IMU data will be combined
"""
feature_emg, feature_imu = [], []
for x in w_emg:
feature = []
for n in range(8):
if feature_set == Constant.georgi:
feature.extend(
Feature_extraction.georgi([y[n] for y in x],
sensor=Constant.EMG))
elif feature_set == Constant.rehman:
feature.extend(Feature_extraction.rehman([y[n] for y in x]))
elif feature_set == Constant.robinson:
feature.extend(Feature_extraction.robinson([y[n] for y in x]))
elif feature_set == Constant.mantena:
feature.extend(Feature_extraction.mantena([y[n] for y in x]))
else:
print("Could not match given feature set")
feature_emg.append(feature)
for x in w_imu:
feature = []
for n in range(9):
if feature_set == Constant.georgi:
feature.extend(
Feature_extraction.georgi([y[n] for y in x],
sensor=Constant.IMU))
elif feature_set == Constant.rehman:
feature.extend(Feature_extraction.rehman([y[n] for y in x]))
elif feature_set == Constant.robinson:
feature.extend(Feature_extraction.robinson([y[n] for y in x]))
elif feature_set == Constant.mantena:
feature.extend(Feature_extraction.mantena([y[n] for y in x]))
else:
print("Could not match given feature set")
feature_imu.append(feature)
features = []
for i in range(len(feature_imu)):
f = []
for x in np.asarray([feature_emg[i], feature_imu[i]]).flatten('F'):
f.extend(x)
features.append(f)
return features
