Correlation of Human Carpal Motion and Electromyogram

인체 수관절 운동과 근전도의 상관관계

  • Received : 2010.04.23
  • Accepted : 2010.07.12
  • Published : 2010.10.01


In this experimental study, we have examined the correlation between a human carpal motion and a surface electromyogram. The carpal motion patterns have been identified and the main muscles involved in the carpal motion have been determined by investigating the anatomical structure of a carpal. The torque acting against the carpal motion has been applied by using a device for carpal rehabilitation training, and the surface electromyogram signal corresponding to the torque at the main muscles has been measured. The root-mean-square (RMS) magnitude of the surface electromyogram signal has been calculated and used to analyze the correlation between the surface electromyogram signal and carpal motion. The experimental results have proved that for carpal torque values below $0.1\;N{\cdot}m$, the RMS magnitude of the surface electromyogram signal is linearly proportional to the carpal torque magnitude and that the carpal torque magnitude is linearly proportional to the cross-sectional area of the carpal muscles. Further, the analysis of the contribution of each muscle to the carpal motion has shown that the contribution of the most dominant muscle is consistently 60%. These three results can be applied to develop more sophisticated devices or robots for carpal rehabilitation training.


Carpal Motion;Electromyogram;Correlation;Rehabilitation Training Device


Supported by : (주)피앤에스미캐닉스


  1. Kizuka, T., Masuda, T., Kiryu, T., Sadoyama, T., 2006, Practical Usage of Surface Electromyogram, Tokyo Denki University Press.
  2. Lee, J. H., Lee, Y. S., Lee, J. O. and Park, S. H., 2007, "Biomechanical Gait Analysis and Simulation on the Normal, Cavus and Flat Foot with Orthotics," Journal of KSME(A), Vol. 31, No. 11, pp. 1115-1123.
  3. Lee, C. S. and Gonzalez, R. V., 2008, "Fuzzy Logic versus a PID Controller for Position Control of a Muscle-like Actuated Arm," Journal of Mechanical Science and Technology, Vol. 22, No. 8, pp. 1475-1482.
  4. An, K. N., Kwak, B. M., Chao, E. Y. and Morrey, B. F., 1984, "Determination of Muscle and Joint Forces: A New Technique to Solve the Indeterminate Problem," Journal of Biomechanical Engineering, ASME, Vol. 106, pp. 364-367.
  5. Nagata, K. and Magatani, K., 2003, "Development of the Assist System to Operate a Computer for the Disabled," Proceedings of the 25th Annual International Conference of the IEEE EMBS, pp. 1666-1669.
  6. Choi, C. M., Han, H. N., Ha, S. D. and Kim, J., 2007, "Development of an EMG-Based Computer Interface for the Physically Handicapped," Human-Computer Interface Conference, pp. 222-227.
  7. Neuman, D. A., 2005, Kinesiology of the Musculoskeletal System, Mosby, Chapter 7.
  8. Mitsubishi, 2008, Mitsubishi Hysteresis Clutch and Brake Manual, pp. 11-12.

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