Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (5): 225-229.doi: 10.11896/jsjkx.190400127

• Artificial Intelligence • Previous Articles     Next Articles

Fatigue Detection System Based on Single Channel EEG Signal

WANG Bo-shi, WU Xiu-cheng, HU Xin-yi, ZHANG Li   

  1. School of Electrical Engineering,Chongqing University,Chongqing 400044,China
  • Received:2019-04-23 Online:2020-05-15 Published:2020-05-19
  • About author:WANG Bo-shi,born in 1997,postgra-duate.His main research interests include brain-computer interface and so on.
    WU Xiu-cheng,born in 1998,postgra-duate.His main research interests include electrical engineering and automation.

PDF (PC)

1885

Abstract: For sudden death in people with high labor intensity,this paper designs a fatigue detection system based on single-channel EEG to realize accurate judgment of the fatigue level in order to make a timely warning for this kind of people.The system uses the TGAM(ThinkGear AM) to collect the original EEG data,transmits the data to the host computer via Bluetooth,and extracts four basic rhythm components (δ,θ,α,β) of the EEG in the host computer.The relative frequency band energies of some rhythms are used as the EEG features characterizing fatigue state,and Fisher discriminant analysis(FDA) and probabilistic neural network(PNN) are used to classify EEG features.Finally,the evaluation results are given.The experimental results show that the designed single-channel EEG-based fatigue detection system can achieve high accuracy of fatigue state detection.

Key words: Basic rhythm, EEG, FDA algorithm, GUI, TGAM EEG module

CLC Number: 

  • TP391.4
[1]WANG R Y.Sports Physiology [M].Beijing:People's Sports Publishing House,2002.
[2]LIU Z Q,SONG X S,WANG P,et al.An Identification Method of Fatigue Driving Based on Eye Features[J].Journal of Chongqing University of Technology(Natural Science),2016,30(10):11-15,33.
[3]MORRIS T L,MILLER J C.Electrooculographic and perfor-mance indices of fatigue during simulated flight [J].Biological Psychology,1996,42(3):343-360.
[4]LAL S K L,CRAIG A.Phyasiological indicators of driver fatigue [C]//Rood Satety Research Policing & Bducation.2000.
[5]ZHANG C,WANG H,FU R.Automated Detection of DriverFatigue Based on Entropy and Complexity Measures [J].IEEE Transactions on Intelligent Transportation Systems,2014,15(1):168-177.
[6]ZHANG L Y,ZHENG C X.Study on the EEG Kolmogorov entropy measure for mental fatigue state [J].Chinese Journal of Biomedical Engineering,2007,2(2):170-176.
[7]ZHAO C L,ZHENG C X,ZHAO M.Research on driving mental fatigue grading based on kernel learning algorithm [J].Journal of Data Acquisition & Processing,2009,24(3):335-339.
[8]DU S X,WU T J.Support Vector Machine Method in Pattern Recognition [J].Journal of Zhejiang University(Engineering Science),2003,37(5):521-527.
[9]ZHAO H,RONG L L,LI X.A new method for designing hie-rarchical support vector machine multi-class classifiers [J].Journal of Computer Applications,2003(5):34-37.
[10]CHEN T,CHEN Z G,YUAN X H,et al.Emotion RecognitionMethod Based on Instantaneous Energy of Electroencephalography[J].Computer Engineering,2019,45(4):196-204.
[11]LIU J L.Design and research of brain-computer interface system based on steady-state visual evoked potential [J].Industrial Control Computer,2011(5):8-9.
[12]SUN Z D.Activate the sleeping brain [M].Heilongjiang Science and Technology Press,2010.
[13]XIAO Z H,YU H,WANG Y C.Unsupervised Machine Learning Based on the Sum of Squares of the Dynamic Deviations[J].Journal of Chongqing University of Technology(Natural Science),2018,32(11):134-139,186.
[14]ZHENG J H.Dictionary of Statistics [M].China StatisticsPress,1995:207.
[15]ZHOU Z H.Machine Learning [M].Tsinghua UniversityPress,2016:53.
[16]LI J J,DING Z S,ZHANG H Y.Analysis of Common Discriminant Classification Methods[J].Journal of Xi'an University of Science and Technology,2007,27(1):138-139.
[17]DING L,ZENG S L.HandwrittenMiaowen Recognition Re-search Based on Probabilistic Neural Network [J] .Journal of Dali University,2018(12).
[18]LIN W,WANG X,ZHENG Y H,et al.Study on feature extraction and recognition of partial discharge signals based on probabilistic neural network [J].Electrical Automation,2018,40(3):64-67.
[19]ZHANG M.Design of Communication Principle Demonstration System Based on Matlab GUI[J].Journal of Experimental Technology and Management,2013,30(9):111-113,127.
[1] YANG Bing-xin, GUO Yan-rong, HAO Shi-jie, Hong Ri-chang. Application of Graph Neural Network Based on Data Augmentation and Model Ensemble in Depression Recognition [J]. Computer Science, 2022, 49(7): 57-63.
[2] Jeffrey ZHENG. Meta Knowledge Intelligent Systems on Resolving Logic Paradoxes [J]. Computer Science, 2022, 49(1): 9-16.
[3] ZHANG Xue-jun, YANG Hao-ying, LI Zhen, HE Fu-cun, GAI Ji-yang, BAO Jun-da. Differentially Private Location Privacy-preserving Scheme withSemantic Location [J]. Computer Science, 2021, 48(8): 300-308.
[4] HE Tao, ZHAO Ting, XU He. Novel Algorithm of Single Image Dehazing Based on Dark Channel Prior [J]. Computer Science, 2021, 48(7): 219-224.
[5] WU Guang-zhi, GUO Bin, DING Ya-san, CHENG Jia-hui, YU Zhi-wen. Cognitive Mechanisms of Fake News [J]. Computer Science, 2021, 48(6): 306-314.
[6] CHAI Bing, LI Dong-dong, WANG Zhe, GAO Da-qi. EEG Emotion Recognition Based on Frequency and Channel Convolutional Attention [J]. Computer Science, 2021, 48(12): 312-318.
[7] JIANG Chen-kai, LI Zhi, PAN Shu-bao, WANG Yong-jun. Collision-free Path Planning of AGVs Based on Improved Dijkstra Algorithm [J]. Computer Science, 2020, 47(8): 272-277.
[8] ZHANG Xu, WANG Li-li, YANG Bo-tao. Heuristic Algorithms for Two-dimensional Irregular Bin Packing Problem with GuillotineConstraints [J]. Computer Science, 2020, 47(5): 212-216.
[9] WANG Xiao-ming,ZHAO Xin-bo. Survey of Construction and Application of Reading Eye-tracking Corpus [J]. Computer Science, 2020, 47(3): 174-181.
[10] GUO Chao, WANG Lei, YIN Ai-hua. Hybrid Search Algorithm for Two Dimensional Guillotine Rectangular Strip Packing Problem [J]. Computer Science, 2020, 47(11A): 119-125.
[11] WANG Yong-quan, SHI Zheng-yu, ZHANG Xiao. Study on Restoration of Electronic Disguised Voice Based on DC-CNN [J]. Computer Science, 2019, 46(8): 183-188.
[12] WANG Shao-hui,ZHANG Yan-xuan,WANG Hua-qun,XIAO Fu,WANG Ru-chuan. Efficient Public-key Searchable Encryption Scheme Against Inside Keyword Guessing Attack [J]. Computer Science, 2019, 46(7): 91-95.
[13] XU Cong, PAN Xiao-dong. Linguistic Multi-attribute Group Decision Making Method Based on Normal Cloud Similarity [J]. Computer Science, 2019, 46(6): 218-223.
[14] CHAI Xin, GAO Yi-han, WU You-xi, LIU Jing-yu. Distinguishing Patterns Mining Based on Density Constraint [J]. Computer Science, 2019, 46(12): 26-30.
[15] FENG Luan-luan, LI Jun-hui, LI Pei-feng, ZHU Qiao-ming. Technology and Terminology Detection Oriented National Defense Science [J]. Computer Science, 2019, 46(12): 231-236.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.