Psychogenic tremor disorders identified using tree‐based statistical algorithms and quantitative tremor analysis | Zendy

Piboolnurak Panida | Zendy; Rothey Natalia | Zendy; Ahmed Anwar | Zendy; Ford Blair | Zendy; Yu Qiping | Zendy; Xu Dong | Zendy; Pullman Seth L. | Zendy

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Psychogenic tremor disorders identified using tree‐based statistical algorithms and quantitative tremor analysis

Author(s) -

Piboolnurak Panida,

Rothey Natalia,

Ahmed Anwar,

Ford Blair,

Yu Qiping,

Xu Dong,

Pullman Seth L.

Publication year - 2005

Publication title -

movement disorders

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.352

H-Index - 198

eISSN - 1531-8257

pISSN - 0885-3185

DOI - 10.1002/mds.20634

Subject(s) - psychogenic disease , statistical analysis , computer science , essential tremor , artificial intelligence , pattern recognition (psychology) , psychology , algorithm , physical medicine and rehabilitation , medicine , mathematics , statistics , psychiatry

Detecting psychogenic tremors (PsychT) is often challenging. As there are no laboratory investigations or imaging techniques that can confirm the diagnosis, PsychT is identified on a clinical basis. We present a tree‐based statistical algorithm derived from quantitative computerized tremor recordings as a novel method to help in the recognition of PsychT. The goal of this study was to show that objective data from computerized tremor recordings, when processed through a tree‐based statistical algorithm, can be used to determine whether a patient can be classified as having PsychT. © 2005 Movement Disorder Society

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