Automatic non-linear analysis of non-invasive writing signals, applied to essential tremor

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• 作者：K. Lopez-de-Ipiñ ; a^a ; ^{karmele.ipina@ehu.es" class="auth_mail" title="E-mail the corresponding author} ; A. Bergareche^b ; ^{jesusalbertobergarecheyarza@osakidetza.net" class="auth_mail" title="E-mail the corresponding author} ; P. de la Riva^b ; M. Faundez-Zanuy^c ; ^{faundez@tecnocampus.cat" class="auth_mail" title="E-mail the corresponding author} ; P.M. Calvo^a ; J. Roure^c ; E. Sesa-Nogueras^c
• 关键词：Non-linear handwriting processing ; Essential tremor diagnosis ; Fractal dimensions ; Entropy
• 刊名：Journal of Applied Logic
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：16
• 期：Complete
• 页码：50-59
• 全文大小：821 K

文摘

Essential tremor (ET) in the western world is the most common movement disorder, and 50–70% of essential tremor cases are estimated to be genetic in origin [14]. This work on selection of nonlinear biomarkers derived from drawings and handwriting is part of a wider cross-study for the diagnosis of essential tremor led by Biodonostia Institute. These biomarkers include not only classic linear features, but also non-linear: fractal dimension and entropy. The presence of integrated features of other diseases such as stress is also analyzed. In future works, these new biomarkers will be integrated with the ones obtained in the wider study of Biodonostia. Note that the use of these methods provide undoubted benefits towards the development of more sustainable, low-cost, high-quality, and non-invasive technologies. These systems are easily adaptable to the user and environment, and can be very useful in real complex environments with regard to a social and economic point of view.