Fatigue Evaluation through Machine Learning and a Global Fatigue Descriptor
Research in physiology and sports science has shown that fatigue, a complex psychophysiological phenomenon, has a relevant impact in performance and in the correct functioning of our motricity system, potentially being a cause of damage to the human organism. Fatigue can be seen as a subjective or o...
Main Authors: | G. Ramos, J. R. Vaz, G. V. Mendonça, P. Pezarat-Correia, J. Rodrigues, M. Alfaras, H. Gamboa |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Journal of Healthcare Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/6484129 |
Similar Items
-
Learning interpretable descriptors for the fatigue strength of steels
by: Ning He, et al.
Published: (2021-03-01) -
Sex differences in muscle fatigue following isokinetic muscle contractions
by: Miguel Gomes, et al.
Published: (2021-04-01) -
Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM
by: Yi Ouyang, et al.
Published: (2008-04-01) -
Machine Learning Approach for Fatigue Estimation in Sit-to-Stand Exercise
by: Andrés Aguirre, et al.
Published: (2021-07-01) -
Polymer gear contact fatigue reliability evaluation with small data set based on machine learning
by: Chen, K., et al.
Published: (2022)