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Method

An EEG monitoring method based on compressed sensing for fatigue driving

Pages 1206-1213 | Received 05 Jun 2023, Accepted 17 Jan 2024, Published online: 31 Jan 2024

References

  • Ba Y, Zhang W, Wang Q, Zhou R, Ren C. 2017. Crash prediction with behavioral and physiological features for advanced vehicle collision avoidance system. Transp Res Part C Emerging Technol. 74:22–33. doi:10.1016/j.trc.2016.11.009.
  • Candes EJ, Romberg J, Tao T. 2006. Robust uncertainty principles: exact signal recognition from highly incomplete frequency information. IEEE Trans Inform Theory. 52(2):489–509. doi:10.1109/TIT.2005.862083.
  • Candes EJ, Tao T. 2005. Decoding by linear programming. IEEE Trans Inform Theory. 51(12):4203–4215. doi:10.1109/TIT.2005.858979.
  • Chaudhuri A, Routray A. 2020. Driver fatigue detection through chaotic entropy analysis of cortical sources obtained from scalp EEG signals. IEEE Trans Intell Transport Syst. 21(1):185–198. doi:10.1109/TITS.2018.289.
  • Chen SS, Donoho DL, Saunders MA. 2001. Atomic decomposition by basis pursuit. SIAM Rev. 43(1):129–159. doi:10.1137/S1064827596304010.
  • Dai Y, Wang X, Li X, Tan Y. 2015. Sparse EEG compressive sensing for web-enabled person identification. Measurement. 74:11–20. 7.008. doi:10.1016/j.measurement.2015.0.
  • Donoho D. 2006. Compressed sensing. IEEE Trans Inform Theory. 52(4):1289–1306. doi:10.1109/TIT.2006.871582.
  • Huang KC, Huang TY, Chuang CH, King JT, Wang YK, Lin CT, Jung TP. 2016. An EEG-based fatigue detection and mitigation system. Int J Neural Syst. 26(4):1650018. doi:10.1142/S0129065716500180.
  • Shi LC, Lu BL. 2013. EEG-based vigilance estimation using extreme learning machines. Neurocomputing. 102(102):135–143. doi:10.1016/j.neucom.2012.02.041.
  • Wang F, Wu S, Ping J, Xu Z, Chu H. 2021a. EEG driving fatigue detection with PDC-based brain functional network. IEEE Sensors J. 21(9):10811–10823. doi:10.1109/JSEN.2021.3058658.
  • Wang Z, Zhao Y, He Y, Zhang J. 2021b. Phase lag index-based graph attention networks for detecting driving fatigue. Rev Sci Instrum. 92(9):094105. doi:10.1063/5.0056139.
  • Williamson A, Lombardi DA, Folkard S, Stutts J, Courtney TK, Connor JL. 2011. The link between fatigue and safety. Accid Anal Prev. 43(2):498–515. doi:10.1016/j.aap.2009.11.011.
  • Xu X, Gu H, Yan S, Pang G, Gui G. 2019. Fatigue EEG feature extraction based on tasks with different physiological states for ubiquitous edge computing. IEEE Access. 7:73057–73064. doi:10.1109/ACCESS.2019.2920014.
  • Zeng K, Yan J, Wang Y, Sik A, Ouyang G, Li X. 2016. Automatic detection of absence seizures with compressive sensing EEG. Neurocomputing. 171:497–502. doi:10.1016/j.neucom.2015.06.076.
  • Zhang C, Wang H, Fu R. 2014a. Automated detection of driver fatigue based on entropy and complexity measures. IEEE Trans Intell Transport Syst. 15(1):168–177. doi:10.1109/TITS.2013.2275192.
  • Zhang Z, Jung TP, Makeig S, Pi Z, Rao BD. 2014b. Spatiotemporal sparse Bayesian learning with applications to compressed sensing of multichannel physiological signals. IEEE Trans Neural Syst Rehabil Eng. 22(6):1186–1197. doi:10.1109/TNSRE.2014.2319334.
  • Zhang Z, Liu X, Wei S, Gan H, Liu F, Li Y, Liu C, Liu F. 2019. Electrocardiogram reconstruction based on compressed sensing. IEEE Access. 7:37228–37237. doi:10.1109/ACCESS.2019.2905000.

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