In this thesis, novel methods of nonlinear system identification and new approaches in physiological modeling and rehabilitation engineering are presented. Thereby, a contribution to the advancement of the repetitive peripheral magnetic stimulation (RPMS) is made. The RPMS is an innovative approach in rehabilitation of sensorimotor deficits like paresis and spasticity, e.g. after stroke.
First, new methods for parameter identification in the presence of linear, nonlinear and separable nonlinear parameterization are introduced. Conditions for parameter convergence are developed using a stability framework from nonlinear dynamic system theory. The proposed theoretic framework is generic and can be applied to a variety of problems. Here, it is used to identify the plant of the RPMS-induced index finger extension and flexion. For this purpose, an adequate biomechanical and neurophysiological model is developed.
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In this thesis, novel methods of nonlinear system identification and new approaches in physiological modeling and rehabilitation engineering are presented. Thereby, a contribution to the advancement of the repetitive peripheral magnetic stimulation (RPMS) is made. The RPMS is an innovative approach in rehabilitation of sensorimotor deficits like paresis and spasticity, e.g. after stroke.
First, new methods for parameter identification in the presence of linear, nonlinear and separable nonlin...
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