Error recognition for rehabilitation and microsurgery

Abstract

Manual positioning error is a significant problem in rehabilitation and surgical applications of human-machine interaction. Effective means for error recognition and suppression can enhance lifestyle independence for persons with movement disorders and improve task performance in microsurgery. This paper describes algorithms for real-time estimation of both tremor and non-tremor components of undesired motion. Applications in command filtering for rehabilitative humanmachine interfaces, and in an intelligent handheld microsurgical instrument for active compensation of error, are also presented. subjects, sources of error include physiological tremor, wander, and jerk. The need for noise or error suppression in microsurgery is relevant to both telerobotic procedures and direct manual operations with hand-held instruments. In vitreoretinal microsurgery, there is a demand for accuracy of 10 pm in instrument positioning [l]. This is generally unattainable without accuracy-enhancement techniques.