Repository for the analysis of the new GMAC measure for upper-limb use. GMAC stands for "gross movement + acivity counts".
This contains the analysis code employed for the paper "GMAC: A simple measure to quantify upper limb use from wrist-worn accelerometers". The paper is currently under review.
Here is the block diagram of the new GMAC algorithm:
The data used in this paper can be obtained from our previously opened dataset from the Upper-Limb Assessment GitHub repository.
After you clone this repository, carry out the following steps to get the data:
- Create a folder called
data
in the root directory of this repository. - Copy the
control
andpatient
data folders intodata
.
Once you do this you are ready to run the analysis code.
The analysis has four notebooks:
01 Pitch Optimization: Notebook for optimizing the parameter for the forearm orientation subblock of the new GMAC algorithm.
02 Accl. Magnitude Optimization: Notebook for optimizing the parameter for estimating the amount of forearm movements subblock of the new GMAC algorithm.
03a Decision Rule Optimization: Notebook for optimizing the parameter of the decision rule block of the new GMAC algorithm.
03b Decision Rule Optimization (Intra-Subject Model): Notebook for optimizing the parameter of the decision rule block of the intra-subject models for the new GMAC algorithm .