SVC ANALYTICS a Software for Plotting and Extracting Features from Online Handwriting Signals

Autor:	Marcos Faundez-Zanuy, Roger Bertran-Capdevila, Enric Sesa-Nogueras
Rok vydání:	2019
Předmět:	business.industry Computer science 05 social sciences Feature extraction 050209 industrial relations Pattern recognition Fractal Software Salient Analytics Handwriting 0502 economics and business Entropy (information theory) Artificial intelligence business 050203 business & management
Zdroj:	TSP
DOI:	10.1109/tsp.2019.8768880
Popis:	In this paper we present a software tool for displaying and analyzing handwriting signals recorded by digitizing devices that capture both in-air and on-surface trajectories. This tool has two salient features: it can visualize the invisible trajectories described by the writing device while it is not exerting any pressure on the writing surface and it can calculate entropies and fractal dimensions, two measures that are relevant when analyzing handwriting signals for health-related purposes, mainly in the diagnose of some neurodegenerative conditions like Parkinson’s disease and Alzheimer’s disease.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c8f27ece8915fd01f1118c8f9bb95359 https://doi.org/10.1109/tsp.2019.8768880 Zobrazit plný text záznamu