kinematic_sensor_argument_validator: Ensure the kinematic sensor arguments are well formed

In Sage-Bionetworks/mhealthtools: mhealthtools - Package for processing mobile sensor data and to extract meaningful features

Description

Verify that the arguments passed to accelerometer_features and gyroscope_features are valid.

Usage

kinematic_sensor_argument_validator(
  sensor_data,
  time_filter,
  detrend,
  sampling_rate,
  frequency_filter,
  IMF,
  window_length,
  window_overlap,
  derived_kinematics,
  funs,
  models
)

Arguments

sensor_data	An n x 4 data frame with column names t, x, y, z containing kinematic sensor (accelerometer or gyroscope) measurements. Here n is the total number of measurements, t is the timestamp of each measurement, and x, y and z are linear axial measurements.
time_filter	A length 2 numeric vector specifying the time range of measurements to use during preprocessing and feature extraction after normalizing the first timestamp to 0. A NULL value means do not filter any measurements.
detrend	A logical value indicating whether to detrend the signal.
sampling_rate	Sampling rate of sensor_data.
frequency_filter	A length 2 numeric vector specifying the frequency range of the signal (in hertz) to use during preprocessing and feature extraction. A NULL value means do not filter frequencies.
IMF	The number of IMFs used during an empirical mode decomposition transformation. The default value of 1 means do not apply EMD to the signal.
window_length	A numerical value representing the length (in number of samples) of the sliding window used during the windowing transformation. Both window_length and window_overlap must be set for the windowing transformation to be applied.
window_overlap	Fraction in the interval [0, 1) specifying the amount of window overlap during a windowing transformation. Both window_length and window_overlap must be set for the windowing transformation to be applied.
derived_kinematics	A logical value specifying whether to add derived kinematic measurements to sensor_data after the transform defined by the above parameters has been applied to the raw sensor measurements.
funs	A function or list of functions that each accept a single numeric vector as input. Each function should return a dataframe of features (normally a single-row datafame, with column names as feature names). The input vectors will be the axial measurements from sensor_data after the transform defined by the above parameters has been applied. If no argument is supplied to either funs or models, a default set of feature extraction functions (as described in default_kinematic_features) will be supplied for this parameter.
models	A function or list of functions that each accept sensor_data as input after the transform defined by the above parameters has been applied and returns features. Useful for functions which compute individual features using multiple input variables.

Value

A list of gyroscope features. The output from funs will be stored under $extracted_features and the output from models will be stored under $model_features. If there is an error during extraction, the returned result will be stored under $error.

Sage-Bionetworks/mhealthtools documentation built on Sept. 20, 2020, 1:42 p.m.