---
license: cc-by-4.0
language:
- en
- es
tags:
- fatigue
- muscle
- EMG
- Cycling
- Biomedical
- time-series
pretty_name: Muscle Fatigue in Cyclist
task_categories:
- time-series-forecasting
---

This dataset was created with healthy participants aged between 18 and 25 years old. The participants in this dataset were not frequent athletes.

The dataset consists of 8 EMG signals recorded from the domineering foot of each participant during a cycling trial. The participants performed exercises on a conditioned cycle, alternating with short periods of high-intensity sprints. When a participant could no longer sustain the sprint intensity, this was considered the first index of fatigue and was labeled as "Transition-to-Fatigue." If the participant was unable to continue the base exercise, it was labeled as "Fatigue."

For this dataset, it is recommended to work with binary classification models, taking the "Transition-to-Fatigue" state as the positive class, as the data in the "Fatigue" class is significantly limited.

**FEATURES**
- Time
- Right Rectus femoris
- Left Gluteus maximus
- Left Gastrocnemius medialis
- Left Semitendinosus
- Left Biceps femoris caput longus
- Right Vastus medialis
- Right Tibialis anterior
- Left Gastrocnemius lateralis

**TARGETS**
- 0-No Fatigue
- 1-Transition To Fatigue
- 2-Fatigue

By: Yomin Jaramillo M