A review of control methods for electric power wheelchairs based on electromyography signals with special emphasis on pattern recognition

IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India)

Volumn 28, Issue 4, 2011, Pages 316-326

  Phinyomark, Angkoon ^a   Phukpattaranont, Pornchai ^a   Limsakul, Chusak ^a  

^a PRINCE OF SONGKLA UNIVERSITY   (Thailand)

Author keywords

Classification; Electric power wheelchair; Electromyography signal; Feature extraction; Hybrid system; Myoelectric control; Pattern recognition

Indexed keywords

ABSOLUTE VALUES; ASSISTIVE TECHNOLOGY; CONTROL COMMAND; CONTROL METHODS; DISABLED PEOPLE; ELECTRIC POWER WHEELCHAIRS; ELECTROMYOGRAPHY SIGNAL; ELECTROMYOGRAPHY SIGNALS; EMG SIGNAL; EMG-BASED CONTROL; FULL CONTROL; HIGH PERFORMANCE CONTROL; LIMB MOVEMENTS; MYOELECTRIC CONTROL; PATTERN RECOGNITION METHOD; QUALITY OF CONTROLS; REAL-TIME OPERATION; RECOGNITION METHODS; RECOGNITION SYSTEMS; REHABILITATION DEVICES; TIME DOMAIN; UPPER LIMBS; WAVE FORMS; ZERO-CROSSINGS;

CONTROL THEORY; ELECTRICITY; FEATURE EXTRACTION; HANDICAPPED PERSONS; HYBRID SYSTEMS; PATTERN RECOGNITION SYSTEMS; TIME DOMAIN ANALYSIS; WHEELCHAIRS;

QUALITY CONTROL;

EID: 80052157409     PISSN: 02564602     EISSN: 09745971     Source Type: Journal    
DOI: 10.4103/0256-4602.83552     Document Type: Review

References (50)

1. L. Fehr, W.E. Langbein, and S.B. Skaar, "Adequacy of power wheelchair control interfaces for persons with severe disabilities: A clinical survey," J. Rehabil. Res. Dev., vol. 37, no. 3. pp. 353-60, May/June 2000. (Pubitemid 30641232)
2. P. Jia, H. Hu, T. Lu, and K. Yuan, "Head gesture recognition for hand-free control of an intelligent wheelchair," Int. J. Ind. Rob., vol. 34, no. 1. pp. 60-8, 2007. (Pubitemid 46122568)
3. S. Nakanishi, Y. Kuno, N. Shimada, and Y. Shirai, "Robotic wheelchair based on observations of both user and environment," in IEEE/RSJ Int. Conf. Intelligent Robots and Systems, Kyongju, Korea, pp. 912-7, 1999. (Pubitemid 30577970)
4. S.P. Levine, D.A. Bell, L.A. Jaros, R.C. Simpson, Y. Koren, and J. Borenstein, "The NavChair assistive wheelchair navigation system," IEEE Trans. Rehabil. Eng., vol. 7, no. 4. pp. 443-51, Dec. 1999. (Pubitemid 30007673)
5. N.I. Katevas, N.M. Sgouros, S.G. Tzafestas, G. Papakonstantinou, P. Beattie, J. M. Bishop, et al., "The autonomous mobile robot SENARIO: A sensor-aided intelligent navigation system for powered wheelchairs," IEEE Rob. Autom. Mag., vol. 4, no. 4. pp. 60-70, Dec. 1997.
6. D.G. Evans, R. Drew, and P. Blenkhorn, "Controlling mouse pointer position using an infrared head-operated joystick," IEEE Trans. Rehabil. Eng., vol. 8, no. 1. pp. 107-17, Mar. 2000. (Pubitemid 30230145)
7. G. Schmeisser, and W. Seamone, "An assistive equipment controller for quadriplegics," Johns Hopkins Med. J., vol. 145, no. 3. pp. 84-8, Sept. 1979. (Pubitemid 10239979)
8. E.D. Coyle, "Electronic wheelchair controller designed for operation by hand-operated joystick, ultrasonic non-contact head control and utterance from a small word-command vocabulary," in IEE Colloquium on New Developments in Electric Vehicles for Disabled Persons, London, UK, pp. 3/1-4, Mar. 1995.
9. R. Barea, L. Boquete, M. Mazo, and E. Lopes, "System for assisted mobility using eye movements based on electrooculography," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 10, no. 4, pp. 209-18, Dec. 2002. (Pubitemid 36207315)
10. K. Tanaka, K. Matsunaga, and H.O. Wang, "Electroencephalogrambased control of an electric wheelchair," IEEE Trans. Rob., vol. 21, no. 4. pp. 762-6, Aug. 2005.
11. M.A. Oskoei, and H. Hu, "Myoelectric control systems - A survey," Biomed. Signal Process. Control, vol. 2, no. 4. pp. 275-94, Oct. 2007.
12. B. Hudgins, P. Parker, and R. Scott, "A new strategy for multifunction myoelectric control," IEEE Trans. Biomed. Eng., vol. 40, no. 1. pp. 82-94, Jan. 1993. (Pubitemid 24060692)
13. R Merletti, P Parker. Electromyography Physiology, Engineering, and Noninvasive Applications. Hoboken, New Jersey: John Wiley and Sons; 2004.
14. O. Fukuda, T. Tsuji, M. Kaneko, and A. Otsuka, "A human-assisting manipulator teleoperated by EMG signals and arm motions," IEEE Trans. Rob. Autom., vol. 19, no. 2. pp. 210-22, Apr. 2003.
15. K. Englehart, B. Hudgins, and P.A. Parker, "A wavelet-based continuous classification scheme for multifunction myoelectric control," IEEE Trans. Biomed. Eng., vol. 48, no. 3. pp. 302-11, Mar. 2001. (Pubitemid 32249578)
16. M. Agarabi, P. Bonato, and C.J. De Luca, "A sEMG-based method for assessing the design of computer mice," in 26th Ann. Int. Conf. IEEE Engineering in Medicine and Biology Society, San Francisco, California, USA, pp. 2450-3, Sept. 2004. (Pubitemid 40035533)
17. Y. Oonishi, S. Oh, and Y. Hori, "A new control method for powerassisted wheelchair based on the surface myoelectric signal," IEEE Trans. Ind. Electron., vol. 57, no. 9. pp. 3191-6, Sept. 2010.
18. M. Zecca, S. Micera, M.C. Carrozza, and P. Dario, "Control of multifunctional prosthetic hands by processing the electromyographic signal," Crit. Rev. Biomed. Eng., vol. 30, no. 4-6. pp. 459-85, 2002. (Pubitemid 36528604)
19. I. Moon, M. Lee, J. Chu, and M. Mun, "Wearable EMG-based HCI for electric-powered wheelchair users with motor disabilities," in IEEE Int. Conf. Robotics and Automation, Barcelona, Spain, pp. 2649-54, Apr. 2005. (Pubitemid 46084188)
20. S.M. Firoozabadi, M.A. Oskoei, and H. Hu, "A human-computer interface based on forehead multi-channel bio-signals to control a virtual wheelchair," in Iranian Conf. Biomedical Engineering, Tehran, Iran, pp. 272-7, 2008.
21. J.U. Chu, I. Moon, and M.S. Mun, "A real-time EMG pattern recognition system based on linear-nonlinear feature projection for a multifunction myoelectric hand," IEEE Trans. Biomed. Eng., vol. 53, no. 11. pp. 2232-9, Nov. 2006. (Pubitemid 44629861)
22. J.U. Chu, I. Moon, Y.J. Lee, S.K. Kim, and M.S. Mun, "A supervised feature-projection-based real-time EMG pattern recognition for multifunction myoelectric hand control," IEEE/ASME Trans. Mechatron., vol. 12, no. 3. pp. 282-90, June. 2007. (Pubitemid 47018779)
23. Y.H. Liu, H.P. Huang, and C.H. Weng, "Recognition of electromyographic signals using cascaded kernel learning machine," IEEE/ASME Trans. Mechatron., vol. 12, no. 3. pp. 253-64, June. 2007.
24. R.N. Khushaba, A. Al-Ani, and A. Al-Jumaily, "Orthogonal fuzzy neighborhood discriminant analysis for multifunction myoelectric hand control," IEEE Trans. Biomed. Eng., vol. 57, no. 6. pp. 1410-9, June. 2010.
25. H.J. Hermens, B. Freriks, C. Disselhorst-Klug, and G. Rau, "Development of recommendations for SEMG sensors and sensor placement procedures," J. Electromyography Kinesiol., vol. 10, no. 5. pp. 361-74, Oct. 2000.
26. C.J. De Luca, "Surface electromyography: Detection and recording" DelSys Incorporated (2002), available from: http://www.delsys. com/Attachments-pdf/WP-SEMGintro.pdf. [Last cited on 2011 Jan 02].
27. A.T. Au, and R.F. Kirsch, "EMG-based prediction of shoulder and elbow kinematics in able-bodied and spinal cord injured individuals," IEEE Trans. Rehabil. Eng., vol. 8, no. 4. pp. 471-80, Dec. 2000. (Pubitemid 32178935)
28. L. Wei, H. Hu, and K. Yuan, "Use of forehead bio-signals for controlling an intelligent wheelchair," in IEEE Int. Conf. Robotics and Biomimetics, Bangkok, Thailand, pp. 108-13, Feb. 2008.
29. V. Rajesh, P.R. Kumar, and D.V. Reddy, "SEMG based human machine interface for controlling wheel chair by using ANN," in Int. Conf. Control, Automation, Communication and Energy Conservation, Perundurai, Tamilnadu, India, pp. 1-6, June. 2009.
30. L. Ozyilmaz, T. Yildirim, and H. Seker, "EMG signal classification using conic section function neural networks," in Int. Joint Conf. Neural Networks, Washington, DC, USA, pp. 3601-3, 1999. (Pubitemid 30593441)
31. J.S. Han, W.C. Bang, and Z.Z. Bien, "Feature set extraction algorithm based on soft computing techniques and its application to EMG pattern classification," Fuzzy Optim. Decis. Making, vol. 1, no. 3. pp. 269-86, 2002.
32. J.S. Han, W.K. Song, J.S. Kim, W.C. Bang, H. Lee, and Z. Bien, "New EMG pattern recognition based on soft computing techniques and its application to control of a rehabilitation robotic arm," in 6th Int. Conf. Soft Computing, Brno University of Technology, Brno, Czech Rep., pp. 890-7, 2000.
33. J.S. Han, Z.Z. Bien, D.J. Kim, H.E. Lee, and J.S. Kim, "Humanmachine interface for wheelchair control with EMG and its evaluation," in 25th Ann. Int. Conf. IEEE Engineering in Medicine and Biology Society, Cancun, Mexico, pp. 1602-5, Sept. 2003.
34. J.S. Han, D.H. Stefanov, K.H. Park, H.B. Lee, D.J. Kim, W.K. Song, et al., "Development of an EMG-based powered wheelchair controller for users with high-level spinal cord injury," in Int. Conf. Control, Automation and System, Jeju, Korea, pp. 503-6, 2001.
35. D.J. Kim, W.K. Song, J.S. Han, and Z. Bien, "Effective intention reading technique as a means of human-robot interaction for human centered systems," in 10th IEEE Int. Conf. Fuzzy Systems, Melbourne, Australia, pp. 1195-8, 2001.
36. Z. Bien, M.J. Chung, P.H. Chang, D.S. Kwon, D.J. Kim, J.S. Han, et al., "Integration of a rehabilitation robotic system (KARES II) with human-friendly man-machine interaction units," Auton. Robots, vol. 16, no. 2. pp. 165-91, 2004.
37. Z. Bien, D.J. Kim, M.J. Chung, D.S. Kwon, and P.H. Chang, "Development of a wheelchair-based rehabilitation robotic system (KARES II) with various human-robot interaction interfaces for the disabled," in IEEE/ASME Int. Conf. Advanced Intelligent Mechatronics, Port Island, Kobe, Japan, pp. 902-7, July. 2003.
38. J.H. Song, J.W. Jung, S.W. Lee, and Z. Bien, "Robust EMG pattern recognition to muscular fatigue effect for powered wheelchair control," J. Intell. Fuzzy Syst., vol. 20, no. 1-2. pp. 3-12, 2009.
39. J.H. Song, J.W. Jung, and Z. Bien, "Robust EMG pattern recognition to muscular fatigue effect for human-machine interaction," in 5th Mexican Int. Conf. Artificial Intelligence, Advances in Artificial Intelligence, New York: Springer-Verlag; vol. 4293, pp. 1190-9, 2006. (Pubitemid 46030714)
40. B. Karlik, M. Tokhi, and M. Alci, "A fuzzy clustering neural network architecture for multifunction upper-limb prosthesis," IEEE Trans. Biomed. Eng., vol. 50, no. 11. pp. 1255-61, Nov. 2003. (Pubitemid 37339400)
41. S.E. Hussein, and M.H. Granat, "Intention detection using a neuro-fuzzy EMG classifier," IEEE Eng. Med. Biol. Mag., vol. 21, no. 6. pp. 123-9, Nov.-Dec. 2002. (Pubitemid 36215915)
42. M. Khezri, and M. Jahed, "Introducing a new multi-wavelet function suitable for sEMG signal to identify hand motion commands," in 29th Ann. Int. Conf. IEEE Engineering in Medicine and Biology Society, Lyon, France, pp. 1924-7, Aug. 2007.
43. M. Vuskovic, and S.J. Du, "Classification of prehensile EMG patterns with simplified fuzzy ARTMAP networks," in Int. Joint Conf. Neural Networks, Honolulu, Hawaii, pp. 2539-44, 2002. (Pubitemid 34648032)
44. K.H. Kim, H.K. Kim, J.S. Kim, W. Son, and S.Y. Lee, "A biosignalbased human interface controlling a power-wheelchair for people with motor disabilities," ETRI J., vol. 28, no. 1. pp. 111-4, Feb. 2006. (Pubitemid 43228276)
45. Y. Huang, K. Englehart, and B. Hudgins, "A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses," IEEE Trans. Biomed. Eng., vol. 52, no. 11. pp. 1801-11, Nov. 2005. (Pubitemid 41578800)
46. M.A. Oskoei, and H. Hu, "Myoelectric based virtual joystick applied to electric powered wheelchair," in IEEE/RSJ Int. Conf. Intelligent Robots and Systems, Nice, France, pp. 2374-9, Sept. 2008.
47. M.A. 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. 1956-65, Aug. 2008. (Pubitemid 352013532)
48. L. Wei, and H. Hu, "EMG and visual based HMI for hands-free control of an intelligent wheelchair," in World Congress on Intelligent Control and Automation, Jinan, China, pp. 1027-32, 2010.
49. A. Phinyomark, C. Limsakul, and P. Phukpattaranont, "EMG feature extraction for tolerance of 50 Hz interference," in 4th Int. Conf. on Engineering Technologies, Novi Sad, Serbia, pp. 289-93, Apr. 2009.
50. A. Phinyomark, C. Limsakul, and P. Phukpattaranont, "A novel feature extraction for robust EMG pattern recognition," J. Comput., vol. 1, no. 1. pp. 71-80, Dec. 2009.