JRM Vol.16 No.5 pp. 482-488
doi: 10.20965/jrm.2004.p0482


An EMG-Controlled Hand Exoskeleton for Natural Pinching

Lenny Lucas*, Matthew DiCicco*, and Yoky Matsuoka*,**

*Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA

**Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 5000 Forbes Ave. NSH3207, Pittsburgh, PA 15213

June 17, 2004
July 16, 2004
October 20, 2004
hand, exoskeleton, orthotics, electromyography, spinal cord injury
Spinal cord and other local injuries often lead to partial paralysis while the brain stays fully functional. When this partial paralysis occurs in the hand, these individuals are not able to execute daily activities on their own even if their arms are functional. To remedy this problem, a lightweight, low-profile orthotic exoskeleton has been designed to restore dexterity to paralyzed hands. The exoskeleton’s movements are controlled by the user’s available electromyography (EMG) signals. The device has two actuators controlling the index finger flexion that can be used to perform a pinching motion against a fixed thumb. Using this orthotic device, a new control technique was developed to allow for a natural reaching and pinching sequence by utilizing the natural residual muscle activation patterns. To design this controller, two actuator control algorithms were explored with a quadriplegic (C5/C6) subject and it was determined that a simple binary control algorithm allowed for faster interaction with objects over a variable control algorithm. The binary algorithm was then used as an enabling algorithm to activate the exoskeleton movements when the natural sequence of muscle activities found a pattern related to a pinch. This natural pinching technique has shown significant promise toward realistic neural control of wearable robotic devices to assist paralyzed individuals.
Cite this article as:
L. Lucas, M. DiCicco, and Y. Matsuoka, “An EMG-Controlled Hand Exoskeleton for Natural Pinching,” J. Robot. Mechatron., Vol.16 No.5, pp. 482-488, 2004.
Data files:
  1. [1] Christopher Reeve Paralysis Foundation.
  2. [2] N. Benjuya, and S. Kenny, “Myoelectric Hand Orthosis,” Journal of Prosthetics and Orthotics, pp. 149-154, 1990.
  3. [3] M. Slack, and D. Berbrayer, “A Myoelectrically Controlled Wrist-Hand Orthosis for Brachial Plexus Injury: A Case Study,” Journal of Prosthetics and Orthotics, pp. 171-174, 1992.
  4. [4] J. B. Makaram, D. K. Dittmer, R. O. Buchal, and D. B. MachArthur, “The SMARTR Wrist-Hand Orthosis (WHO) for Quadriplegic Patients,” Journal of Prosthetics and Orthotics, pp. 73-76, 1993.
  5. [5] K. Kuribayashi, S. Shimizu, K. Okimura, and T. Taniguchi, “A discrimination system using neural networks for EMG-control prostheses-Integral type of emg signal processing,” Proceedings of the 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1750-1755, 1993.
  6. [6] K. Ito, T. Tsuji, A. Kato, and M. Ito, “EMG pattern classification for a prosthetic forarm with three degrees of freedom,” IEEE International Workshop on Robot and Human Communication, pp. 69-74, 1992.
  7. [7] R. F. Kirsh, and A. T. C. Au, “EMG-based motion intention detection for control of a shoulder neuroprosthesis,” IEEE International Conference of the Engineering in Medicine and Biology Society, Vol.5, pp. 1944-1945, 1997.
  8. [8] A. T. C. Au, T. C. Arthur, and R. F. Kirch, “EMG-based prediction of shoulder and elbow kinematics in able-bodied and spinarl cord injured individuals,” IEEE Transactions on Rehabilitation Engineering, Vol.8, pp. 471-480, 2000.
  9. [9] D. C. Johnson, and D. W. Repperger, “Development of a mobility assist for the paralyzed, amputee, and spastic patient,” IEEE, pp. 67-70R, 1996.
  10. [10] Y. Umetani, Y. Yamada, T. Morizono, T. Yoshida, and S. Aoki, “Skil Mate” wearable exoskeleton robot, in Proc. IEEE International Conference on Systems, Man and Cybernetics, Tokyo, Japan, pp. 984-988, 1999.
  11. [11] K. Kuribayashi, M. Takahashi, and T. Taniguchi, “An upper extremity prosthesis using SMA actuator,” IEEE International Workshop on Robot and Human Communication, pp. 52-57, 1992.
  12. [12] M. DiCicco, L. Lucas, and Y. Matsuoka, “Comparison of Two Control Strategies for a Muscle Controlled Orthotic Exoskeleton for the Hand,” The Proceedings of the IEEE Intl. Conference on Robotics and Automation, pp. 1622-1627, 2004.

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