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-lim...

Full description

Saved in:
Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2024-12, Vol.24 (24), p.8081
Main Authors: Cerqueira, Sara M, Vilas Boas, Rita, Figueiredo, Joana, Santos, Cristina P
Format: Article
Language:English
Subjects:
Adult
Algorithms
Data collection
Datasets
dynamic movements
Electromyography
Electromyography - methods
Exercise
Female
Humans
Male
Movement - physiology
Muscle fatigue
Muscle Fatigue - physiology
Muscle, Skeletal - physiology
perceived fatigue
Physical fitness
sEMG
Sensors
Upper Extremity - physiopathology
Young Adult
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24248081