cut_off_signal cuts off the input multi-channel accelerometer data
according to a new dynamic range, then adds gausian noise to the cut-off
cut_off_signal(df, range = NULL, noise_std = 0.03)
dataframe. Input multi-channel accelerometer data.
numerical vector. The new dynamic ranges to cut off the signal.
Should be a 2-element numerical vector.
number. The standard deviation of the added gaussian noise.
dataframe. The multi-channel accelerometer data with the new dynamic
range as specified in
This function simulates the behavior that a low dynamic range device is trying to record high intensity movement, where recorded accelerometer signal will be cut off at the dynamic range, but the true movement should have higher acceleration values than the dynamic range. This function also adds gaussian noise to the cut off samples to better simulate the real world situation.
This function is a utility function that is used to simulate the behaviors of low dynamic range devices during algorithm validation.
# Use sample data for testing df = sample_raw_accel_data # Show df illustrate_signal(df, range=c(-8, 8))# cut off the signal to c(-2, 2) new_df = cut_off_signal(df, range=c(-2, 2), noise_std=0.03) # Show new df illustrate_signal(new_df, range=c(-2, 2))