Abstract
A generalized non-linear mathematical model for the identification of EMG/tension relationship is developed. Volterra functional expansions are utilized for identification of the linearities as well as the non-linearities of the system, leading to the development of a generalized methodology. Kernels of the system are computed in the frequency domain using an efficient fast fourier transform (FFT) algorithm. The results obtained for the case of biceps brachii muscle are compared with the corresponding results obtained by using a stochastic state-space model : the Volterra approach appears to provide a more realistic characterization. Symmetry of the kernels reduces storage requirements and computation time on the digital computer considerably. Physiological interpretation of the results obtained reveals diagnostic information about certain pathologies related to human skeletal muscle.
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