src.event_detection package¶
src.event_detection.imu_event_detection module¶
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src.event_detection.imu_event_detection.gyro_threshold_stance(imu, stance_magnitude_threshold=0.5, stance_count_threshold=8)¶ As presented by Tunca et al. (https://doi.org/10.3390/s17040825). Detect stance phases according to the given gyroscope magnitude, and minimum sample length threshold value.
- Parameters
imu (IMU) – IMU object with data
stance_magnitude_threshold (float) – magnitude threshold
stance_count_threshold (int) – grace period in samples
- Returns
Boolean vector indicating stance phases
- Return type
np.array
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src.event_detection.imu_event_detection.hundza_gait_events(imu)¶ Gait event detection by Hundza et al. (https://doi.org/10.1109/TNSRE.2013.2282080) An example of another gait event detection algorithm.
- Parameters
imu (IMU) – IMU object with data
- Returns
timesteps of different gait events TOFS, IOFS, TO (see Hundza paper) and stance vector
- Return type
tuple[list[float], ..]
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src.event_detection.imu_event_detection.tunca_gait_events(imu, stance_magnitude_threshold, stance_count_threshold)¶ Gait event detection by Tunca et al. (https://doi.org/10.3390/s17040825)
- Parameters
imu (IMU) – IMU object with data
gyro_threshold (float) – gyroscope threshold for identifying stance phases
stance_count_threshold (int) – stance count threshold for identifying stance phases
- Returns
index of IC_samples, FO_samples, timestamps of IC_times, FO_times and stance indicator
- Return type
tuple[list[float], ..]
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src.event_detection.imu_event_detection.zero_crossing(x_1, x_2, y_1, y_2)¶ Helper function: linear interpolation for zero crossing between points (x_1, y_1) and (x_2, y_2).
- Parameters
x_1 (float) – x coordinate point 1
x_2 (float) – x coordinate point 2
y_1 (float) – y coordinate point 1
y_2 (float) – y coordinate point 2
- Returns
x value for zero-crossing point
- Return type
float