Author:
Lucas Lenny, ,DiCicco Matthew,Matsuoka Yoky,
Abstract
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.
Publisher
Fuji Technology Press Ltd.
Subject
Electrical and Electronic Engineering,General Computer Science
Reference12 articles.
1. Christopher Reeve Paralysis Foundation. http://www.apacure.com.
2. N. Benjuya, and S. Kenny, “Myoelectric Hand Orthosis,” Journal of Prosthetics and Orthotics, pp. 149-154, 1990.
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. 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. 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.
Cited by
97 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献