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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