Design an intelligence system for early identification on developmental dyslexia of Chinese language

Abstract

People with dyslexia have difficulties in fluently reading and writing characters which highly affect their learning progress. It is very important to identify dyslexic students that need intervention and extra support during their childhood. However, the waiting time for dyslexia assessment services is often long. To address the above problem, we propose a cloud-based early identification system of dyslexia. We design and develop a mobile app with AWS cloud platform as server. We have identified 27 representative traditional Chinese characters for handwriting data collection. After the first round of the data collection, 66 children aged 5-7 were recruited in Hong Kong. We carry out K-means clustering algorithm to investigate the characteristics of data points on a feature map for each character. We find out that some Chinese words contain more distinguishable characteristics for identifying children with dyslexia. Since children aged 5-7 are still learning how to write traditional Chinese characters properly, children with no risk of dyslexia still have certain possibilities of writing characters with characteristics of handwriting by children with dyslexia. It increases the difficulties of the early identification on developmental dyslexia of Chinese language. Finally, we present our findings and future work.