We propose a system for automatic balance assessment. Acceleration signals acquired by sensors worn by a patient. Multiple medium and high frequency signals systems and inference oppenheim pdf features extraction and selection.
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Building an expert system able to process the feature vector. The paper presents the automatic computer-aided balance assessment system for supporting and monitoring the diagnosis and rehabilitation process of patients with limited mobility or disabled in home environment. The system has adopted seven Berg Balance Scale activities. The assessment approach is based on the accelerometric signals acquired by the inertial sensors worn by the patient. Several specific, mostly medium frequency features of signals are introduced and discussed. The reduction of the feature vector has been performed using the multilevel Fisher’s linear discriminant. The classification employs the multilayer perceptron artificial neural network.
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Check if you have access through your login credentials or your institution. This article concerns signal processing and relation of spectra to time-series. Spectral power density” redirects here. Any signal that can be represented as an amplitude that varies in time has a corresponding frequency spectrum.