Intelligent synthesis of neuromusculoskeletal signals using fuzzy expert critics

Jack M. Winters

doi:10.1117/12.240884

30 May 1996 Intelligent synthesis of neuromusculoskeletal signals using fuzzy expert critics

Jack M. Winters

Proceedings Volume 2718, Smart Structures and Materials 1996: Smart Sensing, Processing, and Instrumentation; (1996) https://doi.org/10.1117/12.240884
Event: 1996 Symposium on Smart Structures and Materials, 1996, San Diego, CA, United States

Abstract

The problem of synthesizing large amounts of sensor data into a meaningful form represents one of the key challenges in making effective use of smart sensors/actuators that are distributed throughout a structure. This paper develops an engineering approach for addressing this problem, focusing on how large sets of neuromusculoskeletal measurements can be synthesized with approximate reasoning by experts and trained human observation to help extract and prioritize the most salient diagnostic findings, given a reasonably large set of strategic performance tasks. A key objective is to create an environment for intimate human- computer interaction, that optimally uses the capabilities of each. The best of two key conceptual frameworks are synthesized: initial design via rule-based fuzzy expert critic modules, followed by a gradual transition toward fuzzy neuro-optimization and neuro- classification modules. It is suggested that this provides a more reasonable approach not only for interactive near-real-time medical diagnosis assisted by a 'smart' computer, but also for developing the types of robust adaptive critics needed for advanced studies of principles underlying neuromotor control and skill acquisition.

Citation Download Citation

Jack M. Winters "Intelligent synthesis of neuromusculoskeletal signals using fuzzy expert critics", Proc. SPIE 2718, Smart Structures and Materials 1996: Smart Sensing, Processing, and Instrumentation, (30 May 1996); https://doi.org/10.1117/12.240884

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