Comparing recognition methods to identify different types of grasps for hand rehabilitation

ACHI 2014 - 7th International Conference on Advances in Computer-Human Interactions

Volumn , Issue , 2014, Pages 109-114

  Leon, Beatriz ^a   Basteris, Angelo ^a   Amirabdollahian, Farshid ^a  

^a UNIVERSITY OF HERTFORDSHIRE   (United Kingdom)

Author keywords

Grasp posture recognition; Neural Networks; Stroke rehabilitation; Support Vector Machines

Indexed keywords

EXOSKELETON (ROBOTICS); HUMAN COMPUTER INTERACTION; INTERACTIVE COMPUTER SYSTEMS; NEURAL NETWORKS; NEUROMUSCULAR REHABILITATION; PATIENT REHABILITATION; SAMPLING; SUPPORT VECTOR MACHINES;

ACTIVITIES OF DAILY LIVING; HAND REHABILITATION; MOVEMENT PERFORMANCE; POSTURE RECOGNITION; RECOGNITION METHODS; STROKE REHABILITATION; SUPPORT VECTOR MACHINE METHOD; WRIST REHABILITATION;

PALMPRINT RECOGNITION;

EID: 84966533790     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. A. A. Timmermans, H. A. Seelen, R. D. Willmann, and H. Kingma, "Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design," J Neuroeng Rehabil, vol. 6, 2009, pp. 1-18.
2. G. B. Prange, H. J. Hermens, J. Schafer, N. Nasr, G. Mountain, A. H. A. Stienen, and F. Amirabdollahian, "Script: Tele-robotics at home - functional architecture and clinical application," in 6th International Symposium on E-Health Services and Technologies (EHST), Geneva, Switzerland, 2012.
3. J. P. Dewald and R. F. Beer, "Abnormal joint torque patterns in the paretic upper limb of subjects with hemiparesis," Muscle Nerve, vol. 24, no. 2, Feb 2001, pp. 273-283.
4. T. Feix, H. bodo Schmiedmayer, J. Romero, and D. Kragic, "A comprehensive grasp taxonomy," in Robotics, Science and systems conference: Workshop on understanding the Human Hand for advancing robotic manipulation, 2009, pp. 1-2.
5. A. Chaudhary, J. L. Raheja, K. Das, and S. Raheja, "Intelligent approaches to interact with machines using hand gesture recognition in natural way: A survey," International Journal of Computer Science and Engineering Survey (IJCSES), vol. 2, no. 1, 2011, pp. 122-133.
6. L. Lamberti and F. Camastra, "Handy: A real-time three color glovebased gesture recognizer with learning vector quantization," Expert Systems with Applications, vol. 39, no. 12, 2012, pp. 10 489-10 494.
7. J. LaViola, "A survey of hand posture and gesture recognition techniques and technology," Brown University, Tech. Rep. CS-99-11, April June 1999.
8. D. Xu, "A neural network approach for hand gesture recognition in virtual reality driving training system of spg," in Pattern Recognition, 2006. ICPR 2006. 18th International Conference on, vol. 3, 2006, pp. 519-522.
9. R. Palm and B. Iliev, "Grasp recognition by time-clustering, fuzzy modeling, and hidden markov models (hmm) - a comparative study," in Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on, 2008, pp. 599-605.
10. C. Systems, "CyberGlove," http://www.cyberglovesystems.com/, [retrived: January, 2014].
11. S. Ates, J. Lobo-Prat, P. Lammertse, H. van der Kooij, and A. Stienen, "Script passive orthosis: Design and technical evaluation of the wrist and hand orthosis for rehabilitation training at home," in ICORR13, 13th International Conference on Rehabilitation Robotics, Seattle, Washington, 2013, pp. 1-6.
12. S. Electronics, "Flex Sensor 2.2"," https://www.sparkfun.com/products/ 10264, [retrived: January, 2014].
13. A. D. Keller, C. L. Taylor, and V. Zahm, Studies to determine the functional requirements for hand and arm prosthesis. Dept. of Engineering, University of California, 1947.
14. N. Yozbatiran, L. Der-Yeghiaian, and S. C. Cramer, "A standardized approach to performing the action research arm test," Neurorehabil Neural Repair, vol. 22, no. 1, 2008, pp. 78-90.
15. J. A. Anderson, An introduction to neural networks. Cambridge, MA: MIT Press, 1995.
16. P. Melin and O. Castillo, "Supervised learning neural networks," in Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing, ser. Studies in Fuzziness and Soft Computing. Springer Berlin Heidelberg, 2005, vol. 172, pp. 55-83.
17. H. Hasan and S. Abdul-Kareem, "Static hand gesture recognition using neural networks," Artificial Intelligence Review, 2012, pp. 1-35.
18. "Neurolab Library," https://code.google.com/p/neurolab/, [retrived: January, 2014].
19. C. Cortes and V. Vapnik, "Support-vector networks," Machine Learning, vol. 20, no. 3, 1995, pp. 273-297.
20. C.-C. Chang and C.-J. Lin, "Libsvm: A library for support vector machines," ACM Trans. Intell. Syst. Technol., vol. 2, no. 3, May 2011, pp. 27:1-27:27.