Motion Detection for Children with Cerebral Palsy Using K-Nearest Neighbor

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Anik Nur Handayani, Dika Fikri Laistulloh, Ilham Ari Elbaith Zaeni, Mohammad Efendi, Rosa Andrie Asmara, Osamu Fukuda

2022 Proceedings - IEIT 2022: 2022 International Conference on Electrical and Information Technology Conference paper Cited by 1 Quartile

Abstract

A disruption in the brain's development in a kid results in the disorder known as cerebral palsy (CP). Treatments including physiotherapy, hydrotherapy, occupational, and speech therapy can all help to lessen the effect. Treatments aim to enhance motor abilities, control flexibility, and enhance motor function patterns. However, the repetitive movements that can be used in traditional physical therapy administered by therapists have limitations. For this reason, researchers are working to develop therapeutic media based on human-machine interaction that can aid in the therapeutic process for children with cerebral palsy. The use of picture data for classification is now possible because to technical advancements. The method used in this research is KNN (K-Nearest Neighbor). KNN is a method used for classification based on data that is most similar to a predetermined number of nearest neighbors. © 2022 IEEE.

Affiliations

Universitas Negeri Malang, Malang, Indonesia; State Polytechnic of Malang, Malang, Indonesia; Saga University, Saga, Japan