This function is used to compute the norm-jerk from triaxial acceleration data.

## Usage

njerk(A, sampling_rate)

## Arguments

A

A tag sensor data list or a nx3 acceleration matrix with columns [ax ay az]. Acceleration can be in any consistent unit, e.g., g or m/s^2. A can be in any frame as the norm-jerk is rotation independent. A must have at least 2 rows (i.e., n>=2).

sampling_rate

The sampling rate in Hz of the acceleration signals. This is used to estimate the differential by a first-order difference.

## Value

The norm-jerk from triaxial acceleration data in the form of a column vector with the same number of rows as in A, or a tag sensor data structure (if the input A was one). The norm-jerk is ||dA/dt||, where ||x|| is the 2-norm of x, i.e., the square-root of the sum of the squares of each axis. If the unit of A is m/s^2, the norm-jerk has unit m/s^3. If the unit of A is g, the norm-jerk has unit g/s. As j is the norm of the jerk, it is always positive or zero (if the acceleration is constant). The final value in j is always 0 because the last finite difference cannot be calculated.

msa, odba
sampleMatrix <- matrix(c(1, 2, 3, 2, 2, 4, 1, -2, 4, 4, 4, 4), byrow = TRUE, nrow = 4, ncol = 3)