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FENG YU, LUO LINTAO. A NONLINEAR FUZZY LINGUISTIC PREDICTION MODEL FOR ACUTE HYPERGLYCEMIA USING CARDIAC ELECTROPHYSIOLOGICAL SIGNALS. J MECH MED BIOL 2021. [DOI: 10.1142/s0219519421400054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
A nonlinear fuzzy linguistic prediction (NFLP) model for acute hyperglycemia prediction is proposed in this paper. The model used IF–THEN expressions which are human-readable and easy to understand. Using cardiac electrophysiological signals as the input, the model can predict actuation durations and concentrations of acute hyperglycemia. The prediction results are compared with the ones of four classical models which are partial least squares (PLS), least-square support vector machine (LSSVM), back-propagation neural network (BPNN) and Takagi–Sugeno (T–S) model. The results show that the proposed method has high prediction accuracy. The method can provide support for clinical diagnosis of acute hyperglycemia.
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Affiliation(s)
- YU FENG
- Shaanxi Provincial Land Engineering Construction Group Co. Ltd., Xi’an, Shaanxi 710075, P. R. China
- School of Electronic and Control Engineering, Chang’an University, Xi’an, Shaanxi 710064, P. R. China
| | - LINTAO LUO
- Shaanxi Provincial Land Engineering Construction Group Co. Ltd., Xi’an, Shaanxi 710075, P. R. China
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