
Detection of Essential Tremor at the $S$ -Band
Author(s) -
Xiaodong Yang,
Syed Aziz Shah,
Aifeng Ren,
Dou Fan,
Nan Zhao,
Dongjian Cao,
Fangming Hu,
Masood Ur Rehman,
Weigang Wang,
Karen M. Von Deneen,
Jie Tian
Publication year - 2018
Publication title -
ieee journal of translational engineering in health and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.653
H-Index - 24
ISSN - 2168-2372
DOI - 10.1109/jtehm.2017.2789298
Subject(s) - bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , signal processing and analysis , robotics and control systems , general topics for engineers
Essential tremor (ET) is a neurological disorder characterized by rhythmic, involuntary shaking of a part or parts of the body. The most common tremor is seen in the hands/arms and fingers. This paper presents an evaluation of ETs monitoring based on finger-to-nose test measurement as captured by small wireless devices working in shortwave or S-band frequency range. The acquired signals in terms of amplitude and phase information are used to detect a tremor in the hands. Linearly transforming raw phase data acquired in the S-band were carried out for calibrating the phase information and to improve accuracy. The data samples are used for classification using support vector machine algorithm. This model is used to differentiate the tremor and nontremor data efficiently based on secondary features that characterize ET. The accuracy of our measurements maintains linearity, and more than 90% accuracy rate is achieved between the feature set and data samples.