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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wang, Y. Winters, J.M. |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Biomed. Eng., Marquette Univ., Milwaukee, WI, USA (Wang, Y.; Winters, J.M.) |
| Abstract | An event-driven dynamic recurrent neuro-fuzzy system for prognosis in rehabilitation is introduced. Four layers are used to implement a fuzzy expert system, each of which consists of a cluster of neurons: input, rule-state, output, and outcome. The input "sensory" layer detects events based on physical and physiological status. Rules can fire in response to events and the current states, generating impulse or pulse-train signals to a given state. The states of the dynamic system, which often represent fuzzy expressions such as "strength.arm", change as a function of time. The event signals and the fuzzy states then are nonlinearly mapped to fuzzy outputs. Outcomes, similar to optimization performance criteria, are then a function of inputs, states and outputs. The system is designed with an interactive graphical user interface to facilitate rule creation by clinical experts. The structure is designed so that reinforcement learning approaches can be added in the future. This will enable tuning of system parameters, based on feedback from the patient and practitioner, as well as the error between predicted and measured outcomes. |
| Sponsorship | Whitaker Found |
| Starting Page | 1256 |
| Ending Page | 1259 |
| File Size | 282743 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780377893 |
| ISSN | 1094687X |
| DOI | 10.1109/IEMBS.2003.1279488 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-09-17 |
| Publisher Place | Mexico |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fuzzy neural networks Adaptive systems Hybrid intelligent systems Neurons Event detection Fires Pulse generation Signal generators Nonlinear dynamical systems Fuzzy systems |
| Content Type | Text |
| Resource Type | Article |
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