Seven Things to Know about Exercise Monitoring with Inertial Sensing Wearables

Overview

This repository presents the implementation of our collaborative project between UPenn/Orthopaedics, UDel/Physical Therapy, and CMU/Engineering on exercise prediction. The manuscript reporting outcomes of this project is published on the IEEE Journal of Biomedical and Health Informatics (JBHI).

The paper is available at this link.

Data

Data were collected from 19 participants performing 37 exercises while wearing 10 inertial measurement units (IMUs) on chest, pelvis, wrists, thighs, shanks, and feet (see the figure below).

You may use data samples in the data to run the code, or download the full dataset on SimTK.

Directory

You may preserve the following directory tree to run the code on your local machine without further modifications.

$ Directory tree
.
├── data\
│   ├── parsed_h5_csv
│   │   └── (IMU data here)
│   └── parsed_joint_angles_all
│       └── (joint angles data here)
├── model\
│   ├── Type1.py
│   ├── Type2.py
│   └── Type3.py
├── utils
│   ├── eval.py 
│   ├── network.py
│   ├── clustering_utils.py
│   ├── preprocessing.py
│   └── visualizer.py
├── constants.py
├── data_processing.py
├── clustering.py
├── main.py
└── tuning.py

Implementation

The implementation was tested with Python 3.8.10 and the following packages:

• numpy 1.22.4
• scipy 1.7.3
• pandas 1.5.3
• scikit-learn 1.2.0
• torch 1.13.1+cu116
• tqdm 4.64.1

In addition, matplotlib 3.6.3 and seaborn 0.12.2 were used for plots.

Guideline

Note: This repository is under active cleaning and update.

Data processing

python data_processing.py

Clustering analysis

python clustering.py

Model evaluation

python main.py

If you use any of the data or code, please cite our paper

V. Phan, K. Song, R. S. Silva, K. G. Silbernagel, J. R. Baxter and E. Halilaj, "Seven Things to Know About Exercise Classification With Inertial Sensing Wearables," in IEEE Journal of Biomedical and Health Informatics, vol. 28, no. 6, pp. 3411-3421, June 2024, doi: 10.1109/JBHI.2024.3368042.