Prosthesis control

KeUer, T. and Popovid, M.R., Real-time stimulation artifact removal in EMG signals for neural prosthesis control appHcations. Proceedings of 6th Annual IFESS Conference, Cleveland, OH, June 10-13,... 

Kuiken, T. A., Dumanian, G. A., Lipschutz, R. D., Miller, L. A., and Stubblefield, K. A. 2004. The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee. Prosthetics Orthotics International, 28,245-253. 

The typical prosthesis control system consists of a Bowden cable with appropriate terminal fittings. The terminal fittings are used to anchor one end of the cable to a body-harness, and the other end to the prosthetic component to be controlled. Between the two end points, the cable crosses the prosthetic joint to be controlled and the physiolog-... 

Childress (1992) presented the following attributes of prosthesis control as desirable. While some of these attributes may be difficult, if not impossible, to achieve in practice, they are stiU seen as desirable goals. 

Prosthesis Control Using Muscle Bulge or Tendon Movement... 

Tendon or residual muscle movement has been used to actuate pneumatic sensors when interposed between a prosthetic socket and the superficial tendons and/or muscle. These sensors can be used for prosthesis control. The Vaduz hand, which was developed by a German team headed by Dr. Edmund Wilms in Vaduz, Liechtenstein, following World War II, used muscle bulge to increase pneumatic pressure to operate a switch-controlled, voluntary-closing, position-servo hand. This hand can be considered to be a forerunner of the pneumatic Otto Bock Hands of the 1970s and the electrically powered Otto Bock Hands of today. 

To put the current state of prosthesis control in the context of the evolution of control in airplanes, automobiles, and remote manipulators, it can be seen that all these fields used similar control meth-... 

Doubler, J. A., and Childress, D. S. (1984b). Design and evaluation of a prosthesis control system based on the concept of extended physiological proprioception. Journal of Rehabilitation Research and Development, vol. 21, no. 1, pp. 19-31. 

Hogan, N. J. (1976). Myoelectric Prosthesis Control Optimal Estimation Applied to EMG and Cybernetic Considerations for Its Use in a Man-Machine Interface. D. dissertation, MIT, Boston, Mass. 

Taylor, D. R., and Finley, F. R (1974) Multiple-Axis Prosthesis Control By Muscle Synergies. In The Control of Upper-Extremity Prostheses and Orthoses, Proceedings of the Conference on the Control of Upper-Extremity Prostheses and Orthoses, Goteborg, Sweden, Oct. 6-8, 1971, Herberts, P., Kadefors, R., Magnusson, R. I., and Petersen, I. (eds.), Charles C. Thomas, Springfield, 111., pp. 181-189. 

Weir, R. F. ff, (1995) Direct Muscle Attachment as a Control Input for a Position Servo Prosthesis Controller. Ph.D. dissertation. Dept, of Biomedical Engineering, Northwestern University, Evanston, DI., June. 

Keywords— prosthesis control, electromyography, fuzzy logic, feature extraction, classification. 

Ajiboye, A., Weir, R. (2005). A heuristic fuzzy logic approach to EMG pattern recognition for multifunction prosthesis control. IEEE Trans, on Biomedical Eng, 52 (11), 280-291. 

The concept of using EMG for prosthesis control started in the 1940s. Electromyographic control is when the signal is used as the input for the control of powered prostheses. 

Table 1 summarizes some of the methods used for feature extraction and classification processes for the ECS based on pattern recognition for upper-limb prosthesis control. It can be seen that the methods used for the feature extraction are varies between TD and TFD method, and it has been reported that there is no superior method between these two processing techniques. As for the classifier, ANN is the most used method to discriminate the final output of the system. 

Table 1 Summary of pattern-recognition based ECS fa- prosthesis control application...

Soares, A. Andrade, E. Lamounier, et. al. (2004) The development of a virtual myoelectric prosthesis controlled by an EMG pattern recognition system based on neural networks, J Intellig Inform Sys, vol. 21, pp.127-141... 

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