Wireless and wearable EEG system for evaluating driver vigilance

IEEE Transactions on Biomedical Circuits and Systems

Volumn 8, Issue 2, 2014, Pages 165-176

  Lin, Chin Teng ^a   Chuang, Chun Hsiang ^a   Huang, Chih Sheng ^a   Tsai, Shu Fang ^a   Lu, Shao Wei ^a   Chen, Yen Hsuan ^a   Ko, Li Wei ^a  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

Brain computer interface; dry electroencephalographic (EEG) system; machine learning; vigilance monitoring

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTOMOBILE DRIVERS; BRAIN; BRAIN COMPUTER INTERFACE; COMPUTER APPLICATIONS; LEARNING SYSTEMS; NEUROPHYSIOLOGY; REGRESSION ANALYSIS; SPECTRUM ANALYSIS;

DRIVING ENVIRONMENT; DRIVING PERFORMANCE; ELECTROENCEPHALOGRAPHIC (EEG); MOBILE APPLICATIONS; POWER SPECTRAL ANALYSIS; TASK PERFORMANCE; VIGILANCE LEVELS; VIGILANCE MONITORING;

ELECTROENCEPHALOGRAPHY;

ATTENTION; BRAIN COMPUTER INTERFACE; CAR DRIVING; CLOTHING; DEVICES; ELECTROENCEPHALOGRAPHY; HUMAN; PHYSIOLOGY; PROCEDURES; SIGNAL PROCESSING; SLEEP STAGE; WIRELESS COMMUNICATION;

ATTENTION; AUTOMOBILE DRIVING; BRAIN-COMPUTER INTERFACES; CLOTHING; ELECTROENCEPHALOGRAPHY; HUMANS; SIGNAL PROCESSING, COMPUTER-ASSISTED; SLEEP STAGES; WIRELESS TECHNOLOGY;

EID: 84902266170     PISSN: 19324545     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBCAS.2014.2316224     Document Type: Article

References (60)

1. F. Vaca, J. S. Harris, H. G. Garrison, and M. P. McKay, "Drowsy driving," Ann. Emerg. Med., vol. 45, no. 4, pp. 433-434, 2005.
2. P. P. Caffier, U. Erdmann, and P. Ullsperger, "Experimental evaluation of eye-blink parameters as a drowsiness measure," Eur. J. Appl. Physiol., vol. 89, no. 3, pp. 319-325, 2003.
3. Q. Ji, Z. Zhu, and P. Lan, "Real-time nonintrusive monitoring and prediction of driver fatigue," IEEE Trans. Veh. Technol., vol. 53, no. 4, pp. 1052-1068, Jul. 2004.
4. J. Horne and L.Reyner, "Vehicle accidents related to sleep: A review," Occupat. Environ. Med., vol. 56, no. 5, pp. 289-294, May 1999.
5. S. K. L. Lal and A. Craig, "A critical review of the psychophysiology of driver fatigue," Biol. Psychol., vol. 55, no. 3, pp. 173-194, Feb. 2001.
6. S.Makeig and T.-P. Jung, "Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness," Cogn. Brain Res., vol. 4, no. 1, pp. 15-25, 1996.
7. S. K. L. Lal and A. Craig, "Driver fatigue: Electroencephalography and psychological assessment," Psychophysiol., vol. 39, no. 3, pp. 313-321, 2002.
8. L. Chin-Teng, C. Che-Jui, L. Bor-Shyh, H. Shao-Hang, C. Chih-Feng, and I. J. Wang, "A real-time wireless brain-computer interface system for drowsiness detection," IEEE Trans. Biomed. Circuits Syst., vol. 4, no. 4, pp. 214-222, Aug. 2010.
9. C. Guger et al., "How many people are able to control a P300-based brain-computer interface (BCI)?," Neurosci. Lett., vol. 462, no. 1, pp. 94-98, Oct. 2009.
10. M. A. Schier, "Changes in EEG alpha power during simulated driving: A demonstration," Internat. J. Psychophysiol., vol. 37, no. 2, pp. 155-162, Aug. 2000.
11. C. Papadelis et al., "Monitoring sleepiness with on-board electrophysiological recordings for preventing sleep-deprived traffic accidents," Clin. Neurophysiol., vol. 118, no. 9, pp. 1906-1922, Sep. 2007.
12. S. Makeig, T.-P. Jung, and T. Sejnowski, "Awareness during drowsiness: Dynamics and electrophysiological correlates," Can. J. Exp. Psychol., vol. 54, no. 4, pp. 266-273, 2000.
13. F.-C. Lin, L.-W. Ko, C.-H. Chuang, T.-P. Su, and C.-T. Lin, "Generalized EEG-based drowsiness prediction system by using a self-organizing neural fuzzy system," IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 59, no. 9, pp. 2044-2055, Sep. 2012.
14. C.-T. Lin et al., "Tonic and phasic EEG and behavioral changes induced by arousing feedback," NeuroImage, vol. 52, no. 2, pp. 633-642, Aug. 2010.
15. C.-T. Lin, C.-H.Chuang, Y.-K.Wang,S.-F. Tsai,T.-C. Chiu, andL.-W. Ko, "Neurocognitive characteristics of the driver: A review on drowsiness, distraction, navigation, and motion sickness," J. Neurosci. Neuroengin., vol. 1, no. 1, pp. 61-81, Jun. 2012.
16. C.-T. Lin, I.-F. Chung, L.-W. Ko, Y.-C. Chen, S.-F. Liang, and J.-R. Duann, "EEG-based assessment of driver cognitive responses in a dynamic virtual-reality driving environment," IEEE Trans. Biomed. Eng., vol. 54, no. 7, pp. 1349-1352, Jul. 2007.
17. C. H. Chuang, L. W. Ko, Y. P. Lin, T. P. Jung, and C. T. Lin, "Independent component ensemble of EEG for brain-computer interface," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 22, no. 2, pp. 230-238, Mar. 2014.
18. T. C. Ferree, P. Luu, G. S. Russell, and D.M. Tucker, "Scalp electrode impedance, infection risk, and EEG data quality," Clin. Neurophysiol., vol. 112, no. 3, pp. 536-544, Mar. 2001.
19. X. Jiawei, R. F. Yazicioglu, B. Grundlehner, P. Harpe, K. A. Makinwa, and C. Van Hoof, "A 160 muW 8-channel active electrode system for EEG monitoring," IEEE Trans. Biomed. Circuits Syst., vol. 5, no. 6, pp. 555-567, Dec. 2011.
20. T. I. Oh et al., "Nanofiber web textile dry electrodes for long-term biopotential recording," IEEE Trans. Biomed. Circuits Syst., vol. 7, no. 2, pp. 204-11, Apr. 2013.
21. G. Gargiulo et al., "A new EEG recording system for passive dry electrodes," Clin. Neurophysiol., vol. 121, no. 5, pp. 686-693, May 2010.
22. T. O. Zander et al., "A dry EEG-system for scientific research and brain-computer interfaces," Front Neurosci., vol. 5, no. 53, pp. 1-10, 2011.
23. Brainwave EEG Signal, NeuroSky, Dec. 5, 2009 [Online]. Available: http://www.neurosky.com
24. C. Grozea, C. D. Voinescu, and S. Fazli, "Bristle-sensors-low-cost flexible passive dry EEG electrodes for neurofeedback and BCI applications," J. Neural. Eng., vol. 8, no. 2, pp. 1-8, Apr. 2011.
25. C.-T. Lin, L.-D. Liao, Y.-H. Liu, I.-J. Wang, B.-S. Lin, and J.-Y. Chang, "Novel dry polymer foam electrodes for long-term EEG measurement," IEEE Trans. Biomed. Eng., vol. 58, no. 5, pp. 1200-1207, 2011.
26. L.-D. Liao et al., "Biosensor technologies for augmented brain-computer interfaces in the next decades," Proc. IEEE, vol. 100, pp. 1553-1566, May 2012, Special Centennial Issue.
27. L.-D. Liao et al., "Gaming control using a wearable and wireless EEGbased brain-computer interface device with novel dry foam-based sensors," J. Neuroeng. Rehabil., vol. 9, no. 5, pp. 1-11, Jan. 2012.
28. L.-D. Liao, I.-J. Wang, S.-F. Chen, J.-Y. Chang, and C.-T. Lin, "Design, fabrication and experimental validation of a novel dry-contact sensor for measuring electroencephalography signals without skin preparation," Sensors, vol. 11, no. 6, pp. 5819-5834, 2011.
29. L. D. Liao et al., "A novel 16-channel wireless system for electroencephalography measurements with dry spring-loaded sensors," IEEE Trans. Instrum. Meas., vol. 63, no. 6, pp. 1545-1555, Jun. 2014.
30. A. J. Smola and B. Schölkopf, "A tutorial on support vector regression," Statist. Comput., vol. 14, no. 3, pp. 199-222, 2004.
31. R.-S. Huang, T.-P. Jung, and S.Makeig, "Tonic changes in EEG power spectra during simulated driving," Lecture Notes Comput. Sci., vol. 5638 LNAI, pp. 394-403, 2009.
32. C.-T. Lin, I. F. Chung, L.-W. Ko, Y.-C. Chen, S.-F. Liang, and J.-R. Duann, "EEG-based assessment of driver cognitive responses in a dynamic virtual-reality driving environment," IEEE Trans. Biomed. Eng., vol. 54, no. 7, pp. 1349-1352, Jul. 2007.
33. W. Karlen, C. Mattiussi, and D. Floreano, "Sleep and wake classification with ECG and respiratory effort signals," IEEE Trans. Biomed. Circuits Syst., vol. 3, no. 2, pp. 71-78, Apr. 2009.
34. M. A. Haberman and E. M. Spinelli, "A multichannel EEG acquisition scheme based on single ended amplifiers and digital DRL," IEEE Trans. Biomed. Circuits Syst., vol. 6, no. 6, pp. 614-618, Dec. 2012.
35. D. Neamen, Microelectronics Circuit Analysis and Design, 3rd ed. New York, NY, USA: McGraw-Hill, 2007.
36. S. Makeig and M. Inlow, "Lapses in alertness: Coherence of fluctuations in performance and EEG spectrum," Electroencephalogr. Clin. Neurophysiol., vol. 86, no. 1, pp. 23-35, Jan. 1993.
37. A. Alenezi, S. A. Moses, and T. B. Trafalis, "Real-time prediction of order flowtimes using support vector regression," Comput. Operat. Res., vol. 35, no. 11, pp. 3489-3503, 2008.
38. U. Thissen, M. Pepers, B. Üstün, W. J. Melssen, and L.M. C. Buydens, "Comparing support vectormachines to PLS for spectral regression applications," Chemometr. Intell. Lab. Syst., vol. 73, no. 2, pp. 169-179, 2004.
39. C.-C. Chang and C.-J. Lin, "LIBSVM: A Library for support vector machines," ACM Trans. Intell. Syst. Technol., vol. 2, no. 3, pp. 1-27, Apr. 2011.
40. L. Sheiner and S. Beal, "Some suggestions for measuring predictive performance," J. Pharmacok. Biopharm., vol. 9, no. 4, pp. 503-512, 1981.
41. H. J. Moller, L. Kayumov, E. L. Bulmash, J. Nhan, and C. M. Shapiro, "Simulator performance, microsleep episodes, and subjective sleepiness: Normative data using convergent methodologies to assess driver drowsiness," J. Psychosom. Res., vol. 61, no. 3, pp. 335-42, Sep. 2006.
42. M. Ferrara and L. D. Gennaro, "How much sleep do we need?," Sleep Med. Rev., vol. 5, no. 2, pp. 155-179, Apr. 2001.
43. R. S. Huang, T. P. Jung, and S. Makeig, "Tonic changes in EEG power spectra during simulated driving," Lecture Notes Comput. Sci., vol. 5638 LNAI, pp. 394-403, Dec. 2009.
44. S. Banks, P. Catcheside, L. Lack, R. R. Grunstein, and R. D. McEvoy, "Low levels of alcohol impair driving simulator performance and reduce perception of crash risk in partially sleep deprived subjects," Sleep, vol. 27, no. 6, pp. 1063-1067, Sep. 2004.
45. B. T. Jap, S. Lal, P. Fischer, and E. Bekiaris, "Using EEG spectral components to assess algorithms for detecting fatigue," Expert Syst. Applicat., vol. 36, no. 2, pp. 2352-2359, Mar. 2009.
46. A. Campagne, T. Pebayle, and A. Muzet, "Correlation between driving errors and vigilance level: Influence of the driver's age," Physiol. Behav., vol. 80, no. 4, pp. 515-524, Jan. 2004.
47. H. J. Eoh, M. K. Chung, and S.-H. Kim, "Electroencephalographic study of drowsiness in simulated driving with sleep deprivation," Int. J. Ind. Ergonom., vol. 35, no. 4, pp. 307-320, 2005.
48. S. Otmani, T. Pebayle, J. Roge, and A. Muzet, "Effect of driving duration and partial sleep deprivation on subsequent alertness and performance of car drivers," Physiol. Behav., vol. 84, no. 5, pp. 715-724, 2005.
49. Rules of the Road,4th ed. Road Safety Authority, 2013.
50. C.-T. Lin, C.-H. Chuang, C.-S. Huang, Y.-H. Chen, and L.-W. Ko, "Real-time assessment of vigilance level using an innovative Mindo4 wireless EEG system," in Proc. IEEE Int. Symp. Circuits and Systems, 2013, pp. 1528-1531.
51. J. R.Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, no. 6, pp. 767-791, Jun. 2002.
52. F. v. d. Heijden, R. Duin,D. d.Ridder, and D. M. J. Tax, Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Hoboken, NJ, USA: Wiley, 2004.
53. Cognionics Cognionics, Dec. 5, 2013 [Online]. Available: http://cognionics.com
54. Enobio Neuroelectrics, Dec. 5, 2013 [Online]. Available: http://neuroelectrics. com/enobio
55. DSI 10/20 Quasar, Dec. 5, 2013 [Online]. Available: http://www. quasarusa.com
56. Wireless Low-Power Active-Electrode EEG Headset, IMEC, Dec. 5, 2013 [Online]. Available: http://www2.imec.be
57. Y. M. Chi, C. Maier, and G. Cauwenberghs, "Ultra-high input impedance, low noise integrated amplifier for noncontact biopotential sensing," IEEE J. Emerg. Sel. Topics Circuits Syst., vol. 1, no. 4, pp. 526-535, 2011.
58. G. Ruffini et al., "ENOBIO dry electrophysiology electrode; first human trial plus wireless electrode system," in Proc. IEEE Eng. Med. Biol. Soc. Conf., 2007, pp. 6690-6694.
59. NeuroSky BrainWave Signal (EEG) of NeuroSky, Inc. [Online]. Available: http://frontiernerds.com/files/neurosky-vs-medical-eeg.pdf
60. J.R. Estepp, J. W. Monnin, J.C.Christensen, and G. F.Wilson, "Evaluation of a dry electrode system for electroencephalography: Applications for psychophysiological cognitive workload assessment," in Proc. Human Factors and Ergonom. Soc. Annu. Meeting, 2010, pp. 210-214.