Muscle computer interfaces for driver distraction reduction

Computer Methods and Programs in Biomedicine

Volumn 110, Issue 2, 2013, Pages 137-149

  Khushaba, Rami N ^a   Kodagoda, Sarath ^a   Liu, Diaki ^a   Dissanayake, Gamini ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

Driver distraction; Electromyogram (EMG); Signal processing

Indexed keywords

COMPUTATIONALLY EFFICIENT; DISCRIMINANT FEATURE EXTRACTION; DISCRIMINATIVE FEATURES; DRIVER DISTRACTIONS; ELECTROMYOGRAM; MOTOR-VEHICLE CRASHES; REAL-TIME EXPERIMENT; SINGULARITY PROBLEMS;

AUTOMOBILE ELECTRONIC EQUIPMENT; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; SIGNAL PROCESSING; WHEELS;

ACCIDENTS;

ACCURACY; ADULT; ARTICLE; BODY POSTURE; CAR DRIVING; COMPUTER INTERFACE; CONTROLLED STUDY; DISTRACTIBILITY; ELECTROMYOGRAM; FEMALE; FUZZY NEIGHBORHOOD DISCRIMINANT ANALYSIS; GEOMETRY; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; MALE; PERCEPTION; SENSOR; SIGNAL TRANSDUCTION;

ACCIDENTS, TRAFFIC; ADULT; ALGORITHMS; AUTOMOBILE DRIVING; AUTOMOBILES; BAYES THEOREM; DISCRIMINANT ANALYSIS; ELECTRODES; ELECTROMYOGRAPHY; FEMALE; FINGERS; FUZZY LOGIC; HAND; HUMANS; MALE; MUSCLES; PATTERN RECOGNITION, AUTOMATED; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; YOUNG ADULT;

EID: 84875907357     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2012.11.002     Document Type: Article

References (53)

1. Treat J.R. A study of precrash factors involved in traffic accidents. HSRI Research Review 1980, 10(6):35.
2. Lee J.D., Young K.L., Regan M.A. Defining driver distraction. Driver Distraction: Theory Effects and Mitigation 2009, 31-40. CRC Press. M.A. Regan, J.D. Lee, K.L. Young (Eds.).
3. Nevile M., Haddington P. In-car Distractions and their Impact on Driving Activities 2010, Department of Infrastructure and Transport, Road Safety Grant Report RSGR-2010-001.
4. McEvoy S.P. Look what I can do while I'm driving: implications for road safety in Australia. Medical Journal of Australia 2007, 187:428-429.
5. S.G. Klauer, T.A. Dingus, V.L. Neale, J.D. Sudweeks, D.J. Ramsey, The impact of driver inattention on near-crash/crash risk: an analysis using the 100-car naturalistic driving study data, Report No. DOT HS 810 954, National Highway Traffic Safety Administration, Washington, DC, 2006.
6. Dong Y., Hu Z., Uchimura K., Murayama N. Driver inattention monitoring system for intelligent vehicles: a review. IEEE Transactions on Intelligent Transportation Systems 2011, 12(2):596-614.
7. T.A. Ranney, E. Mazzae, R. Garrott, M.J. Goodman, NHTSA driver distraction research: past, present, and future, Technical report, Vehicle Test and Research Center, East Liberty, OH, July 2000.
8. Pickering C.A., Burnham K.J., Richardson M.J. A review of automotive human machine interface technologies and techniques to reduce driver distraction. Proceedings of the 2nd Institution of Engineering and Technology International Conference on System Safety, London 2007, 223-228.
9. Driver distraction trends and issues. Computing and Control Engineering Journal 2005, 16(1):28-30.
10. Stutts J., Reinfurt D., Staplin L., Rodgman E. The Role of Driver Distraction in Traffic Crashes 2001, AAA Foundation for Traffic Safety, Available at http://www.aaafoundation.org/pdf/distraction.pdf.
11. D.J. Beirness, Distracted driving: the role of survey research, Presented at the International Conference on Distracted Driving, Toronto, Canada, October 2-5, 2005.
12. Zhaosheng Y., Shoufeng L., Chuanjiu W. Human-computer interface design for an in-vehicle information system. Proceedings of the IEEE Intelligent Transportation Systems, vol. 2 2003, 1417-1421.
13. Champoux B. A mode of interaction for driver vehicle interface (DVI). Proceedings of the IEEE Intelligent Vehicles Symposium 2005, 795-800.
14. Cairnie N., Ricketts I.W., McKenna S.J., McAllister G. A prototype adaptive finger-pointing interface for operating secondary controls in motor vehicles. Proceedings of IEEE International Conference on Systems, Man and Cybernetics, vol. 2 2000, 937-942.
15. Pickering C.A. Gesture recognition driver controls. Computing and Control Engineering Journal 2005, 16(1):26-27.
16. Pickering C.A. The search for a safer driver interface: a review of gesture recognition human machine interface. Computing and Control Engineering Journal 2005, 16(1):34-40.
17. Piechulla W., Mayser C., Gehrke H., Konig W. Reducing drivers mental workload by means of an adaptive man-machine interface. Transportation Research Part F 2003, 6(4):233-248.
18. Hansen J.H.L., Wooil K., Angkititrakul P. Advances in human-machine systems for in-vehicle environments. Proceedings of the Hands-free Speech Communication and Microphone Arrays 2008, 128-131.
19. Cheng S.Y., Trivedi M.M. Vision-based infotainment user determination by hand recognition for driver assistance. IEEE Transactions on Intelligent Transportation Systems 2010, 11(3):759-764.
20. Tran C., Doshi A., Trivedi M.M. Pedal error prediction by driver foot gesture analysis: a vision-based inquiry. Proceedings of the IEEE Intelligent Vehicles Symposium, vol. IV 2011, 577-582.
21. Merletti R., Parker P.A. Electromyography Physiology, Engineering, and Noninvasive Applications, IEEE Press Series in Biomedical Engineering 2004, John Wiley and Sons Inc., Hoboken, NJ.
22. Englehart K., Hudgins B. A robust real-time control scheme for multifunction myoelectric control. IEEE Transactions on Biomedical Engineering 2003, 50(7):848-854.
23. Saponas T.S., Tan D.S., Morris D., Balakrishnan R. Demonstrating the feasibility of using forearm electromyography for muscle-computer interfaces. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI) 2008.
24. Saponas T.S., Tan D.S., Morris D., Turner J., Landay J.A. Making muscle-computer interfaces more practical. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI) 2010.
25. Du S., Vuskovic M. Temporal vs. spectral approach to feature extraction from prehensile EMG signals. The IEEE International Conference on Information Reuse and Integration (IEEE IRI-2004) 2004, 344-350.
26. Oskoei M.A., Hu H. Myoelectric control systems - a survey. Biomedical Signal Processing and Control 2007, 2(4):275-294.
27. Khushaba R.N., Al-Jumaily A., Al-Ani A. Novel feature extraction method based on fuzzy entropy and wavelet packet transform for myoelectric control. Proceedings of the 7th International Symposium on Communications and Information Technologies ISCIT 2007, 352-357.
28. Oskoei M.A., Hu H. Support vector machine-based classification scheme for myoelectric control applied to upper limb. IEEE Transactions on Biomedical Engineering 2008, 55(8):1956-1965.
29. Smith R.J., Tenore F., Huberdeau D., Etienne-Cummings R., Thakor N.V. Continuous decoding of finger position from surface EMG signals for the control of powered prostheses. Proceedings of the 30th Annual International Conference of the IEEE EMBS 2008, 197-200.
30. Smith R.J., Huberdeau D., Tenore F., Thakor N.V. Real-time myoelectric decoding of individual finger movements for a virtual target task. Proceedings of the 31st Annual International Conference of the IEEE EMBS 2009, 2376-2379.
31. Peleg D., Braiman E., Yom-Tov E., Inbar G.F. Classification of finger activation for use in a robotic prostheses arm. IEEE Transactions on Biomedical Engineering 2002, 10(4):290-293.
32. Tsenov G., Zeghbib A.H., Palis F., Shoylev N., Mladenov V. Neural networks for online classification of hand and finger movements using surface EMG signals. Proceedings of the 8th Seminar on Neural Network Applications in Electrical Engineering 2006, 167-171.
33. Tenore F., Ramos A., Fahmy A., Acharya S., Etienne-Cummings R., Thakor N.V. Toward the control of individual fingers of a prosthetic hand using surface EMG signals. Proceedings of the 29th Annual International Conference of the IEEE EMBS 2007, 6146-6149.
34. Tenore F.V.G., Ramos A., Fahmy A., Acharya S., Etienne-Cummings R., Thakor N.V. Deconding of individual finger movements using surface electrmyography. IEEE Transactions on Biomedical Engineering 2009, 56(5):1427-1434.
35. Smith R.J., Tenore F., Huberdeau D., Etienne-Cummings R., Thakor N.V. Continuous decoding of finger position from surface EMG signals for the control of powered prostheses. Proceedings of the 30th Annual International Conference of the IEEE EMBS 2008, 197-200.
36. Chu J.U., Moon I., Mun M.S. A supervised feature projection for real-time multifunction myoelectric hand control. Proceedings of the 28th IEEE EMBS Annual International Conference 2006, 2417-2420.
37. K. Englehart, Signal representation for classification of the transient myoelectric signal, PhD dissertation, Department of Electrical and Computer Engineering, University of New Brunswick, New Brunswick, Canada, 1998.
38. Chan A.D.C., Green G.C. Myoelectric control development toolbox. Proceedings of the 30th Conference of the Canadian Medical and Biological Engineering Society 2007, M0100.
39. Khushaba R.N., Al-Ani A., Al-Jumaily A. Orthogonal fuzzy neighborhood discriminant analysis for multifunction myoelectric hand control. IEEE Transactions on Biomedical Engineering 2010, 57(6):1410-1419.
40. Ye J., Janardan R., Li Q., Park H. Feature reduction via generalized uncorrelated linear discriminant analysis. IEEE Transactions on Knowledge and Data Engineering 2006, 18(10):1312-1322.
41. Cai D., He X., Zhou K., Han J., Bao H. Locality sensitive discriminant analysis. Proceedings of the International Joint Conference on Artificial Intelligence 2007, 708-713.
42. He X., Yan S., Hu Y., Niyogi P., Zhang H.J. Face recognition using Laplacianfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 2005, 27(3):328-340.
43. Xiaofei H., Deng C., Shuicheng Y., Zhang H.J. Neighborhood preserving embedding. Proceedings of the 10th IEEE International Conference on Computer Vision 2005, 1208-1213.
44. Yu H., Yang J. A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recognition 2001, 34:2067-2070.
45. Chen L.F., Liao H.Y.M., Ko M.T., Lin J.C., Yu G.J. A new LDA-based face recognition system which can solve the small sample size problem. Pattern Recognition 2000, 33:1713-1726.
46. Ye J. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. Journal of Machine Learning Research 2005, 6:483-502.
47. Chang C.C., Lin C.J. LIBSVM: A Library for Support Vector Machines 2001, Available at http://www.csie.ntu.edu.tw/cjlin/libsvm/.
48. Chen Z.P., Jiang J.H., Li Y., Liang Y.Z., Yu R.Q. Fuzzy linear discriminant analysis for chemical data sets. Chemometrics and Intelligent Laboratory Systems 1999, 45(1-2):295-302.
49. Hargrove L., Englehart K., Hudgins B. A comparison of surface and intramuscular myoelectric signal classification. IEEE Transactions on Biomedical Engineering 2007, 54(5):847-853.
50. Huang H., Zhou P., Li G., Kuiken T.A. An analysis of EMG electrode configuration for targeted muscle reinnervation based neural machine interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2008, 16(1):37-45.
51. Shibanoki T., Shima K., Tsuji T., Otsuka A., Chin T. A Novel channel selection method based on partial KL information measure for EMG-based motion classification. Proceedings of the 13th IFMBE international Conference on Biomedical Engineering, vol. 23, track 1 2009, 694-698.
52. MacIsaac D.T., Parker P.A., Englehart K.B., Rogers D.R. Fatigue estimation with a multivariable myoelectric mapping function. IEEE Transactions on Biomedical Engineering 2006, 53(4):694-700.
53. Fougner A., Scheme E., Chan A.D.C., Englehart K., Stavdahl O. Resolving the limb position effect in myoelectric pattern recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2011, 19(6):644-651.