Authors
Yang, XiaodongShah, Syed Aziz
Ren, Aifeng
Fan, Dou
Zhao, Nan
Cao, Dongjian
Hu, Fangming
Ur-Rehman, Masood
Wang, Weigang
von Deneen, Karen M.
Tian, Jie
Issue Date
2018-01-24
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Show full item recordAbstract
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 [Formula: see text]-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 [Formula: see text]-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.Citation
Yang X, Shah SA, Ren A, Fan D, Zhao N, Cao D, Hu F, Ur Rehman M, Wang W, Von Deneen KM, Tian J (2018) 'Detection of essential tremor at the S-band.', IEEE Journal of Translational Engineering in Health and Medicine, 6 (), pp.-.PubMed ID
29456897PubMed Central ID
PMC5808945Additional Links
https://ieeexplore.ieee.org/document/8268080https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808945/
Type
ArticleLanguage
enISSN
2168-2372EISSN
2168-2372Sponsors
This work was supported in part by the National Natural Science Foundation of China under Grant 61671349, in part by the Fundamental Research Funds for the Central Universities, and in part by the International Scientific and Technological Cooperation and Exchange Projects in Shaanxi Province under Grant 2017KW-005.ae974a485f413a2113503eed53cd6c53
10.1109/JTEHM.2017.2789298
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