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Automatic non-linear analysis of non-invasive writing signals, applied to essential tremor
- Source :
- Journal of Applied Logic. 16:50-59
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- 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.
- Subjects :
- Essential tremor
Logic
business.industry
Computer science
Applied Mathematics
Non invasive
02 engineering and technology
Machine learning
computer.software_genre
medicine.disease
03 medical and health sciences
Nonlinear system
0302 clinical medicine
Handwriting
0202 electrical engineering, electronic engineering, information engineering
medicine
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 15708683
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- Journal of Applied Logic
- Accession number :
- edsair.doi...........0ac655e485d73855dd207b8118a3deb0
- Full Text :
- https://doi.org/10.1016/j.jal.2015.02.003