A comprehensive dataset of surface electromyography and self-perceived fatigue levels for muscle fatigue analysis
Muscle fatigue is a risk factor for injuries in athletes and workers. This brings relevance to the study of this biochemical process to allow for its identification and prevention. This paper presents a novel dataset for muscle fatigue analysis comprising surface electromyography data from upper-limbs and the subject`s self-perceived fatigue level. This dataset contains 13 h and 20 min of data from 13 participants performing a total of 12 upper-limb dynamic movements (8 uni-articular and 4 complex/compound). This dataset may contribute to the testing of new fatigue detection algorithms and analysis of the underlying mechanisms.
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| Notations: | biological and medical sciences training science technical and natural sciences |
| Tagging: | data mining |
| Published in: | Sensors |
| Language: | English |
| Published: |
2024
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| Online Access: | https://doi.org/10.3390/s24248081 |
| Volume: | 24 |
| Issue: | 24 |
| Pages: | 8081 |
| Document types: | article |
| Level: | advanced |