Masahito Katsuki, Junko Kawahara, Hiroyuki Senda, Chinami Yamagishi, Satoshi Mizusawa, Yasuhide Ueki, Shin Kawamura, Kenta Kashiwagi, Akihito Koh, Rie Hashiba, Atsuko Ono, Yuki Watabe, Kazuhiro Ando, Bumpei Kikuchi, Shinya Yamashita, Fuminori Yamagishi
School-Based Stroke Education Through On-Demand E-learning During Coronavirus Disease 2019 Pandemic: Itoigawa Stroke Awareness Campaign
Cureus
dysgraphia neurodevelopmental disorder specific handwriting classical diagnosis based evaluation speed quality final handwritten text therefore delayed conducted handwriting mastered addition highly languagedependent always easily accessible work presents solution able anticipate dysgraphia screening handwriting learned yet order prevent negative consequences individuals academic daily life quantitatively measure handwritingrelated characteristics monitor evolution time leveraged playdrawwrite ipad application collect data produced children last year kindergarten second year elementary school developed metamodel based deep learning techniques ensemble techniques quasisvm receives input raw signals collected processing phase based dimensionality reduction techniques autoencoder time2vec mathematical tools highlevel feature extraction procrustes analysis final dysgraphia classifier identify atrisk children 8462 accuracy 100 precision two years earlier current diagnostic techniques