Freezing of Gait Detection Considering Leaky Wave Cable

Abstract

A novel study on monitoring and analysis of debilitating condition of patients suffering from neurological disorder is presented. Parkinson's disease is characterized by limited motor-ability of a patient. Freezing-of-gait is a major non-motor condition among ageing patients and its evaluation can reduce the chances of any secondary disorders. In this work, amplitude and phase information of the radio signals observed for a fixed period of time are used to differentiate the motor and non-motor symptoms. The amplitude information is classified using support vector machine while linear transformation is applied to obtain sanitized phase information for detection. The proposed method is highly cost effective and very handy with minimum deployment overhead. The analysis shows that this method also offers a high accuracy level of around 99% based on the observation of a number of patients. These features make it an attractive solution for real-time patient monitoring systems.

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“…The SVM algorithm was used to evaluate the performance of the proposed framework, and the results indicated an accuracy of 100% considering the two classes. In general, the system can be considered as an effective complement of the existing mechanism …”

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