Todo: To be extended to cover the two other scripts
scriptDualTask.py takes as an input the data files (in .csv format) related to the HF protocols for both with and without the use of exoskeleton. Datafile names should be provided with .csv extension. Condition data file (in .yaml format) related to the execution time for ascending/descending task is also required as an input.
It then computes the related metrics. It also optionally accepts the output folder name.
2 other algorithms are also proposed, uei and lpp (to be detailed).
python3 is used.
Under Linux, a standard installation in a local environment is obtained using:
python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install -e src/pi_hf
# once done
deactivate
Under Windows:
py -m venv venv
.\venv\Scripts\activate
pip install -U --upgrade pip
pip install -e .\src\pi_hf
# once done
deactivate
Using the reference data provided with the repository, one can call (assuming folder out exists):
run_dualtask test/dualtask/input/subject_1_platformData_exo.csv test/dualtask/input/subject_1_platformData_noexo.csv test/dualtask/input/subject_1_condition.yaml out
# if the python package, has not been installed as indicated
python3 src/pi_hf/pi_hf/scriptDualTask.py -edf test/dualtask/input/subject_1_platformData_exo.csv -ndf test/dualtask/input/subject_1_platformData_noexo.csv --condition test/dualtask/input/subject_1_condition.yaml --output_folder out
# use py instead of python3 under windowsSimilarly:
run_lpp test/lpp/input/inputs_1_LPP.csv out
# if package not installed (if input_file is not indicated, will read from command line)
python3 src/pi_hf/pi_hf/scriptLPP.py --input_file test/lpp/input/inputs_1_LPP.csv --output_folder out
run_uei test/uei/input/inputs_1_UEI.csv out
# if package not installed (if input_file is not indicated, will read from command line)
python3 src/pi_hf/pi_hf/scriptUEI.py --input_file test/uei/input/inputs_1_UEI.csv --output_folder outNote that the uei script expect values already preprocessed (i.e values in [1,2,3]).
To use raw data:
run_uei test/uei/input/inputs_1_UEI_raw.csv False outThe use of Docker image is only available for Linux machine
Caution: (only tested under Linux)
Run the following command in order to create the docker image for this PI:
docker build . -t pi_sbs_hfAn image ready to be used is available on Docker Hub, and can be directly installed and used:
docker pull eurobenchtest/pi_sbs_human_factorAssuming test/input contains the input data, and that the directory out/ is already created, and will contain the PI output:
docker run --rm -v $PWD/test/dualtask/input:/in -v $PWD/out:/out pi_sbs_hf run_dualtask /in/subject_1_platformData_exo.csv /in/subject_1_platformData_noexo.csv /in/subject_1_condition.yaml /out
docker run --rm -v $PWD/test/lpp/input:/in -v $PWD/out:/out pi_sbs_hf run_lpp /in/inputs_1_LPP.csv /out
docker run --rm -v $PWD/test/uei/input:/in -v $PWD/out:/out pi_sbs_hf run_uei /in/inputs_1_UEI.csv /outA simple tool is proposed to collected the questionnaire data, for the lpp and uei protocol.
The tool can be installed as a regular python package:
# follow the guidelines provided above to set and activate a virtual environment
pip install -e src/questionnaire
run_questionnaire
A web page is mounted at direction: http://127.0.0.1:5000/.
Follow the indication to enter the questionnaire values and generate the csv files needed to feed the lpp and uei scripts.
Supported by Eurobench - the European robotic platform for bipedal locomotion benchmarking. More information: Eurobench website
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 779963.
The opinions and arguments expressed reflect only the author‘s view and reflect in no way the European Commission‘s opinions. The European Commission is not responsible for any use that may be made of the information it contains.