Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/717070
Title: Freezing of Gait Detection Considering Leaky Wave Cable
Other Titles: IEEE Transactions on Antennas and Propagation
Authors: Xiaodong Yang|Syed Aziz Shah|Aifeng Ren|Nan Zhao|Zhiya Zhang|Dou Fan|Jianxun Zhao|Weigang Wang|Masood Ur-Rehman
subject: leaky wave cable (LWC)|radio propagation|Antennas|freezing of gait (FOG)|Parkinson’s disease (PD)
Year: -1-Uns- -1
Abstract: 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.
URI: http://localhost/handle/Hannan/717070
ISBN: 0018-926X
volume: Volume
issue: Issue
Appears in Collections:New Ieee 2019

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Title: Freezing of Gait Detection Considering Leaky Wave Cable
Other Titles: IEEE Transactions on Antennas and Propagation
Authors: Xiaodong Yang|Syed Aziz Shah|Aifeng Ren|Nan Zhao|Zhiya Zhang|Dou Fan|Jianxun Zhao|Weigang Wang|Masood Ur-Rehman
subject: leaky wave cable (LWC)|radio propagation|Antennas|freezing of gait (FOG)|Parkinson’s disease (PD)
Year: -1-Uns- -1
Abstract: 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.
URI: http://localhost/handle/Hannan/717070
ISBN: 0018-926X
volume: Volume
issue: Issue
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08509611.pdf3.86 MBAdobe PDFThumbnail
Preview File
Title: Freezing of Gait Detection Considering Leaky Wave Cable
Other Titles: IEEE Transactions on Antennas and Propagation
Authors: Xiaodong Yang|Syed Aziz Shah|Aifeng Ren|Nan Zhao|Zhiya Zhang|Dou Fan|Jianxun Zhao|Weigang Wang|Masood Ur-Rehman
subject: leaky wave cable (LWC)|radio propagation|Antennas|freezing of gait (FOG)|Parkinson’s disease (PD)
Year: -1-Uns- -1
Abstract: 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.
URI: http://localhost/handle/Hannan/717070
ISBN: 0018-926X
volume: Volume
issue: Issue
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08509611.pdf3.86 MBAdobe PDFThumbnail
Preview File