compute_orientation returns a dataframe with accelerometer orientations estimated by Mizell, 2003 for the input dataframe.

compute_orientation(df, estimation_window = 2, unit = "deg")

Arguments

df

dataframe. Input multi-channel signal. First column should be timestamps in POSIXt format.

estimation_window

number. window size in seconds to be used to estimate orientations. Default is 2 (seconds), as suggested by Mizell, 2003.

unit

string. The unit of orientation angles. Can be "deg" (degree) or "rad" (radian). Default is "deg".

Value

dataframe. The returned dataframe will have the same format as input dataframe.

Details

This function accepts a dataframe (in mhealth accelerometer data format) and computes the estimated acclerometer orientations (in x, y, and z angles) for every estimation_window seconds of the entire sequence, and outputs the mean of these angles. The returned dataframe will have the same format as input dataframe, including four columns, and have the same datetime format as input dataframe in the timestamp column. The orientation estimation method used in the function is based on Mizell, 2003.

How is it used in mims-unit algorithm?

This function is used in function (aggregate_for_orientation).

See also

Other transformation functions: sum_up(), vector_magnitude()

Examples

# Use first 10 second sample data for testing df = sample_raw_accel_data df = clip_data(df, start_time = df[1,1], stop_time = df[1, 1] + 600) # compute orientation angles in degrees compute_orientation(df)
#> HEADER_TIME_STAMP X_ANGLE Y_ANGLE Z_ANGLE #> 1 2016-01-15 11:00:00.013 10.98163 90.54295 100.8922
# compute orientation angles in radian angles compute_orientation(df, unit='rad')
#> HEADER_TIME_STAMP X_ANGLE Y_ANGLE Z_ANGLE #> 1 2016-01-15 11:00:00.013 0.1916657 1.580273 1.760901