Confidence-based rejection for improved pattern recognition myoelectric control

IEEE Transactions on Biomedical Engineering

Volumn 60, Issue 6, 2013, Pages 1563-1570

  Scheme, Erik J ^a   Hudgins, Bernard S ^a   Englehart, Kevin B ^a  

^a UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

Amputee; electromyography (EMG); myoelectric; myoelectric signal; pattern recognition; prostheses

Indexed keywords

AMPUTEE; ELECTROMYOGRAPHY (EMG); LINEAR DISCRIMINANT ANALYSIS; MYOELECTRIC; MYOELECTRIC CONTROL; MYOELECTRIC SIGNALS; REJECTION THRESHOLD; TARGET ACQUISITION;

ARTIFICIAL LIMBS; ELECTROMYOGRAPHY; PATTERN RECOGNITION; PATTERN RECOGNITION SYSTEMS; PROSTHETICS;

MYOELECTRICALLY CONTROLLED PROSTHETICS;

ARTICLE; ELECTROMYOGRAPHY; HUMAN; LINEAR DISCRIMINANT ANALYSIS; LINEAR SYSTEM; MOTION; MYOELECTRIC CONTROL; RECOGNITION; TASK PERFORMANCE; VELOCITY;

ADULT; ALGORITHMS; AMPUTEES; ARTIFICIAL LIMBS; BAYES THEOREM; DISCRIMINANT ANALYSIS; ELECTROMYOGRAPHY; HAND STRENGTH; HUMANS; LINEAR MODELS; MIDDLE AGED; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; TASK PERFORMANCE AND ANALYSIS; WRIST;

EID: 84877885479     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2013.2238939     Document Type: Article

References (29)

1. L. Hargrove, K. Englehart, and B. Hudgins, "The effect of electrode displacements on pattern recognition based myoelectric control," presented at the IEEE Eng. Med. Biol. Soc. Conf., New York, USA, 2006.
2. L. Hargrove, K. Englehart, and B. Hudgins, "A training strategy to reduce classification degradation due to electrode displacements in pattern recognition based myoelectric control," Biomed. Signal Process. Control, vol. 3, pp. 175-180, 2008.
3. A. Young, L. Hargrove, and T. Kuiken, "The effects of electrode size and orientation on the sensitivity of myoelectric pattern recognition systems to electrode shift," IEEE Trans. Biomed. Eng., vol. 58, no. 9, pp. 2537-2543, Sep. 2011.
4. A. Young and L. Hargrove, "Strategies to reduce myoelectric pattern recognition sensitivity to electrode shift," presented at the 18th Congr. Int. Soc. Electrophysiol. Kinesiology, Aalborg, Denmark, 2010.
5. E. Scheme, A. Fougner, E. Stavdahl, A. Chan, and K. Englehart, "Examining the adverse effects of limb position on pattern," in Proc. IEEE Eng. Med. Biol. Soc. Conf., Aug./Sep. 2010, pp. 6337-6340.
6. A. Fougner, E. Scheme, A. Chan, K. Englehart, and E. Stavdahl, "Resolving the limb position effect in myoelectric pattern recognition," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 19, no. 6, pp. 644-651, Dec. 2011.
7. E. Scheme, K. Biron, and K. Englehart, "Improving myoelectric pattern recognition positional robustness using advanced training protocols," in Proc. IEEE Eng. Med. Biol. Soc. Conf., Aug./Sep. 2011, pp. 4828-4831.
8. P. Artemiadis and K. Kyriakopoulos, "An EMG-based robot control scheme robust to time-varying EMG signal features," IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 3, pp. 582-588, May 2010.
9. G. Y. , P. Zhou, and G. Li, "Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees," J. NeuroEng. Rehab., vol. 9, no. 74, 2012, Available: http://www.jneuroengrehab.com/content/9/1/74/abstract.
10. R. Kato, T. Fujita, H. Yokoi, and T. Arai, "Adaptable EMG prosthetic hand using on-line learning method: Investigation of mutual adaptation between human and adaptable machine," in Proc. 15th IEEE Int. Symp. Robot Human Interactive Commun., Los Alamitos, CA, USA, 2006, pp. 599-604.
11. P. Kaufmann, K. Englehart, and M. Platzner, "Fluctuating EMG signals: Investigating long-term effects of pattern matching algorithms," in Proc. IEEE Eng. Med. Biol. Soc. Conf., Buenos Aires, Argentina, 2010, pp. 6357-6360.
12. K. Englehart and B. Hudgins, "A robust, real-time control scheme for multifunction myoelectric control," IEEE Trans. Biomed. Eng., vol. 50, no. 7, pp. 848-854, Jul. 2003.
13. M. Golfarelli, D. Maio, and D. Maltoni, "On the error-reject trade-off in biometric verification system," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 786-796, Jul. 1997. (Pubitemid 127762272)
14. C. Chow, "On optimum recognition error and reject tradeoff," IEEE Trans. Inf. Theory, vol. IT-16, no. 1, pp. 41-46, Jan. 1970.
15. G. Fumera and F. Roli, "Analysis of error-reject trade-off in linearly combined multiple classifiers," Pattern Recognit., vol. 37, pp. 1245-1265, 2004. (Pubitemid 38549823)
16. R. Herbei and M. H. Wegkamp, "Classification with reject option," Can. J. Stat., vol. 4, no. 4, pp. 709-721, 2006.
17. C. Landgrebe, D. Tax, P. Paclik, and R. Duin, "The interaction between classification and reject performance for distance-based reject-option classifiers," Pattern Recognit. Lett., vol. 27, no. 8, pp. 908-917, 2006.
18. L. Hargrove, E. Scheme, K. Englehart, and B. Hudgins, "Multiple binary classifications via linear discriminant analysis for improved controllability of a powered prosthesis," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 18, no. 1, pp. 49-57, Jan. 2010.
19. E. Scheme, K. Englehart, and B. Hudgins, "Selective classification for improved robustness of myoelectric control under nonideal conditions," IEEE Trans. Biomed. Eng., vol. 58, no. 6, pp. 1698-1705, Jun. 2011.
20. E. Scheme and K. Englehart, "Validation of a selective ensemble-based classification scheme for myoelectric control using a three dimensional Fitts' law test," Trans. Neural Syst. Rehabil. Eng., vol. PP, no. 9, pp. 1-8, doi: 10.1109/TNSRE.2012.2226189.
21. A. Simon, L. Hargrove, B. Lock, and T. Kuiken, "Target achievement control test: Evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses," J. Rehabil. Res. Dev., vol. 48, no. 6, pp. 619-628, 2011.
22. M. Williams and R. Kirsch, "Evaluation of head orientation and neck muscle EMG signals as command inputs to a human-computer interface for individuals with high tetraplegia," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 16, no. 5, pp. 485-496, Oct. 2008.
23. M. Oskoei and H. Hu, "Support vector machine-based classification scheme for myoelectric control applied to upper limb," IEEE Trans. Biomed. Eng., vol. 55, no. 8, pp. 1956-1965, Aug. 2008. (Pubitemid 352013532)
24. H. Huang, F. Zhang, Y. Sun, and H. He, "Design of a robust EMG sensing interface for pattern recognition," J. Neural Eng., vol. 7, no. 5, pp. 1-10, 2010.
25. O. Fukuda, T. Tsuji, M. Kaneko, and A. Otsuka, "A human-assisting manipulator teleoperated by EMG signals and arm motions," IEEE Trans. Robot. Autom., vol. 2, no. 19, pp. 210-222, Apr. 2003.
26. J. W. Sensinger, B. A. Lock, and T. A. Kuiken, "Adaptive pattern recognition of myoelectric signals: Exploration of conceptual framework and practical algorithms," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 17, no. 3, pp. 271-278, Jun. 2009.
27. P. Fitts, "The information capacity of the human motor system in controlling the amplitude of movement," J. Exp. Psychol., vol. 47, pp. 381-391, 1954.
28. L. Miller and S. Swanson, "Summary and recommendations of the Academy's state of the science conference on upper limb prosthetic outcome measures," J. Prosthetics Orthotics, vol. 21, no. 9, pp. 83-89, 2009.
29. M. Nadeem, J. D. Zucker, and B. Hanczar, "Accuracy-rejection curves (ARCs) for comparing classification methods with a reject option," in JMLR: Workshop Conf. Proc., 2010, pp. 65-81.