Iranian Journal of Biomedical Engineering (IJBME)
نشریه علمی مهندسی پزشکی زیستی

Analysis and Processing of Electroencephalogram Signals in Diagnosis of Fatigue during Neurofeedback Training

Document Type : Full Research Paper

Authors

Maryam Dorvashi 1
Neda Behzadfar 2

1 M.Sc., Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

2 Assistant Professor, Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

https://doi.org/10.22041/ijbme.2022.538155.1718
Abstract
Early detection of fatigue helps to improve the quality and effectiveness of neurofeedback training. Diagnosis of fatigue using the EEG signal of participants during neurofeedback training in 10 training sessions is reviewed in this paper. Neurofeedback training has two different neurofeedback training protocols called protocols one and two. The first protocol is a training feature, a combination of frequency and non-frequency features, but the second protocol only includes frequency features. In the first fatigue time protocol, the slope trend of the power changes of the second low alpha sub-band in the OZ channel is decreasing and the permutation entropy in the FZ channel is increasing. The slope of the score changes is also decreasing. In the second protocol, the slope trend of power changes is the second low alpha sub-band in the OZ channel and decreases the score, in other words, the lack of feature change in line with the goal of neurofeedback training is due to fatigue and the participant cannot score. The results are based on the power slope trend of the second lower alpha sub-band and permutation entropy, which indicates that fatigue occurs for one participant in the first protocol and for three participants in the second protocol.

Keywords

Electroencephalogram
Fatigue
Neurofeedback Training
Power of Lower
Signal Processing
Subjects
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Iranian Journal of Biomedical Engineering (IJBME)
Volume 15, Issue 4
Winter 2022
Pages 289-298

  • Receive Date 03 September 2021
  • Revise Date 09 January 2022
  • Accept Date 09 February 2022

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