Objective To study the characteristics of electroencephalogram (EEG) in fighter pilot selection and to provide physiological basis for optimization of EEG selection standard. Methods 13,461 male high school students aged 18–20 years who participated in the recruitment of fighter pilots from 2019 to 2021 were selected. The proportion of normal, suspicious and abnormal EEG parameters in the candidates was analyzed. Results The proportion of standard characteristic parameters of EEG in normal group, suspicious abnormal group and abnormal group was as follows: ①The basic dominant rhythm of EEG (8-12 Hz) was normal 77.04%, suspicious abnormal group 19.02%, abnormal group 3.94%; ②The proportion of α amplitude difference in frontal area was normal 70.09%, suspicious abnormal 26.52% and abnormal 3.39%, in left and right central (top) area was normal 36.77%, suspicious abnormal 58.19%, abnormal 5.04%, in left and right occipital area was normal 21.71%, suspicious abnormal 73.43%, abnrmal 4.86%; ③The proportion of high amplitude in the right and left occipital regions was normal 15.44%, suspicious abnormal 65.69% and abnormal 18.87%; ④the ratio of right and left occipital areas in 6 Hz rhythm was 14.06% normal, 83.38% suspicious abnormal, and 2.56% abnormal; ⑤The proportion of hyperventilation induction was normal 32.98%, suspicious abnormal 65.18%, abnormal 1.84%; ⑥The proportion of intermittent flash induced was 47.7% normal, 51.43% suspicious abnormal and 0.87% abnormal. Conclusion The abnormal rate of EEG was low, which was in line with the rule of recruitment over the years. The high rate of suspicious abnormalities suggests that the EEG selection criteria need to be quantified more accurately to improve the overall selection effect.


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    Titel :

    Analysis of EEG Characteristics of Male High School Students Who Participated in Fighter Pilot Selection During 2019–2021


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Long, Shengzhao (Herausgeber:in) / Dhillon, Balbir S. (Herausgeber:in) / Chen, Yongsheng (Autor:in)

    Kongress:

    International Conference on Man-Machine-Environment System Engineering ; 2023 ; Beijing, China October 20, 2023 - October 23, 2023



    Erscheinungsdatum :

    2023-09-05


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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