A new method for muscular visual fatigue detection using electrooculogram. (April 2020)

• Record Type: Journal Article
• Authors: Song, Mengchuang; Li, Lina; Guo, Jintao; Liu, Tian; Li, Shuyin; Wang, Yingtuo; Qurat ul ain, ; Wang, Jue
• Is Part Of: Biomedical signal processing and control. Volume 58(2020)
• Publication Date: 2020-04
• Subjects: CFF Critical Fusion Frequency -- MVF Muscular Visual Fatigue -- EOG Electrooculogram -- ERLH Energy Ratio of Low Frequency to High Frequency -- WPBF Wavelet Packet Barycenter Frequency -- ABT Average Blink Time -- ABE Average Blink Energy -- rERLH Correlation Coefficient between CFF and ERLH -- rWPBF Correlation Coefficient between CFF and WPBF -- rABT Correlation Coefficient between CFF and ABT -- rABE Correlation Coefficient between CFF and ABE -- SVM Support Vector Machine -- SD Standard Deviation -- HARS The Hamilton Anxiety Rating Scale -- VDT Video Display Terminals -- SNR Signal-to-Noise Ratio -- VEOG Vertical Electrooculogram -- HEOG Horizontal Electrooculogram -- NS_WPBF Normalized and Standardized WPBF -- NS_ABT Normalized and Standardized ABT -- RBF Radial Basis Function -- ROC Receiver Operating Characteristic Curve -- AUC Area under Curve -- PST Paired Sample T Test -- MF Median Frequency -- EMG Electromyography; Critical fusion frequency -- Electrooculogram physiological indicators -- Support vector machine classifying -- Muscular visual fatigue detection; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2020.101865
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract: Objective: Muscular visual fatigue (MVF)is increasingly common in clinic; However, there is no objective and effective means for the detection of muscular visual fatigue. This study focuses on a new method for muscular visual fatigue detection based on electrooculogram (EOG). Methods: We analyzed the mechanism that develops muscular visual fatigue and designed an experiment to induce muscular visual fatigue intentionally. And we recorded electrooculogram and critical fusion frequency (CFF) in the process. Then we got four electrooculogram physiological indicators and correlation between them and critical fusion frequency was analyzed. Finally, the indicators tendency, statistical difference and support vector machine (SVM) analysis were carried out. Results: The work shows that both wavelet packet barycenter frequency (WPBF) and average blink time (ABT) are significantly correlated with critical fusion frequency, tendency of both them has a good consistency, there is a significant difference for them both before and after muscular visual fatigue and that the trained support vector machine has a classification accuracy of 0.796 (SD 0.172) for states before and after muscular visual fatigue. Conclusion: Wavelet packet barycenter frequency and average blink time can be used for muscular visual fatigue detection, a certain degree of muscular visual fatigue occurred after induction and the trained support vector machine can achieve a good classification detection. We conclude that wavelet packet barycenter frequency and average blink time can be used for accurate muscular visual fatigue detection. Significance: This study is of great significance in muscular visual fatigue prevention and treatment.