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Front Physiol. 2019 Jan 17;9:1947. doi: 10.3389/fphys.2018.01947. eCollection 2018.

Discrete Cosine Transform for the Analysis of Essential Tremor.

Author information

1
Data and Signal Processing Research Group, University of Vic-Central University of Catalonia, Barcelona, Spain.
2
Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
3
Seidor Labs, Tona, Spain.
4
EleKin Research Group, System Engineering and Automation Department, University of the Basque Country UPV/EHU, Donostia, Spain.
5
Neurodegenerative Disorders Area, Biodonostia Health Research Institute, San Sebastián, Spain.
6
Movement Disorders Unit, Department of Neurology, University Hospital Donostia, San Sebastián, Spain.
7
Biomedical Research Networking Centre Consortium for the area of Neurodegenerative Diseases (CIBERNED), Madrid, Spain.

Abstract

Essential tremor (ET) is the most common movement disorder. In fact, its prevalence is about 20 times higher than that of Parkinson's disease. In addition, studies have shown that a high percentage of cases, between 50 and 70%, are estimated to be of genetic origin. The gold standard test for diagnosis, monitoring and to differentiate between both pathologies is based on the drawing of the Archimedes' spiral. Our major challenge is to develop the simplest system able to correctly classify Archimedes' spirals, therefore we will exclusively use the information of the x and y coordinates. This is the minimum information provided by any digitizing device. We explore the use of features from drawings related to the Discrete Cosine Transform as part of a wider cross-study for the diagnosis of essential tremor held at Biodonostia. We compare the performance of these features against other classic and already analyzed ones. We outperform previous results using a very simple system and a reduced set of features. Because the system is simple, it will be possible to implement it in a portable device (microcontroller), which will receive the x and y coordinates and will issue the classification result. This can be done in real time, and therefore without needing any extra job from the medical team. In future works these new drawing-biomarkers will be integrated with the ones obtained in the previous Biodonostia study. Undoubtedly, the use of this technology and user-friendly tools based on indirect measures could provide remarkable social and economic benefits.

KEYWORDS:

archimedes' spiral; automatic drawing analysis; automatic feature selection; discrete cosine features; essential tremor

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