Freezing of Gait Detection Considering Leaky Wave Cable

A novel study on monitoring and analysis of the debilitating condition of patients suffering from the neurological disorder is presented. Parkinson's disease is characterized by limited motor ability of a patient. Freezing of gait is a major nonmotor condition among aging patients and its evaluation can reduce the chances of any secondary disorders. In this paper, amplitude and phase information of the radio signals observed for a fixed period of time are used to differentiate the motor and nonmotor symptoms. The amplitude information is classified using a support vector machine, while the linear transformation is applied to obtain sanitized phase information for detection. The proposed method is very handy with the 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.