Original Publication

Papakostas, Michalis, et al. "Physical fatigue detection through EMG wearables and subjective user reports: a machine learning approach towards adaptive rehabilitation." Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments. ACM, 2019.

Bibtec

@inproceedings{papakostas2019physical, title={Physical fatigue detection through EMG wearables and subjective user reports: a machine learning approach towards adaptive rehabilitation}, author={Papakostas, Michalis and Kanal, Varun and Abujelala, Maher and Tsiakas, Konstantinos and Makedon, Fillia}, booktitle={Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments}, pages={475--481}, year={2019}, organization={ACM} }

EMG_Fatigue_Monitoring

Dependencies:

pyAudioAnalysis

Keras - optional for CNN classification

Run to train & evaluate:

python FatigueMonitoring

Edit the code under the main function to run different evaluation scenarios

Processed Dataset used for this study available in the repo

Original Dataset available at: https://www.dropbox.com/s/daj4du1ra5zo821/Fatigue%20Data.zip?dl=0

Data format

1. experiment_comparison folder contains temporal evaluations in the format : c1:timestamp c2:ground_truth c3:predicted

2. Study1_medfilt11_EMG folder contains the processed EMG measurments by a median filter with window size of 11 samples

3. original_labels_Study1 folder contains the labels provided by the human subjects: 0=NO_FATIGUE, 1=FATIGUE

4. original_times_Study1 folder contains the timestamps of each EEG measurment

5. For questions in the code check the comments

6. Dataset file format: <user_id><exercise_id><repetition_id>

Original Publication

Papakostas, Michalis, et al. "Physical fatigue detection through EMG wearables and subjective user reports: a machine learning approach towards adaptive rehabilitation." Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments. ACM, 2019.

Bibtec

@inproceedings{papakostas2019physical, title={Physical fatigue detection through EMG wearables and subjective user reports: a machine learning approach towards adaptive rehabilitation}, author={Papakostas, Michalis and Kanal, Varun and Abujelala, Maher and Tsiakas, Konstantinos and Makedon, Fillia}, booktitle={Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments}, pages={475--481}, year={2019}, organization={ACM} }