Research Article
Predicting Humans’ Balance Disorder Based on Center of Gravity Using Support Vector Machine
@INPROCEEDINGS{10.1007/978-3-030-93179-7_3, author={Tran Anh Vu and Hoang Quang Huy and Nguyen Viet Dung and Nguyen Phan Kien and Nguyen Thu Phuong and Pham Thi Viet Huong}, title={Predicting Humans’ Balance Disorder Based on Center of Gravity Using Support Vector Machine}, proceedings={Context-Aware Systems and Applications. 10th EAI International Conference, ICCASA 2021, Virtual Event, October 28--29, 2021, Proceedings}, proceedings_a={ICCASA}, year={2022}, month={1}, keywords={Vestibular disorder Center of Gravity (CoG) Data analysis SVM}, doi={10.1007/978-3-030-93179-7_3} }- Tran Anh Vu
Hoang Quang Huy
Nguyen Viet Dung
Nguyen Phan Kien
Nguyen Thu Phuong
Pham Thi Viet Huong
Year: 2022
Predicting Humans’ Balance Disorder Based on Center of Gravity Using Support Vector Machine
ICCASA
Springer
DOI: 10.1007/978-3-030-93179-7_3
Abstract
Currently, vestibular disorders are quite common in Vietnam. However, as far as we know, methods for vestibular diagnosis are only qualitative, which are mostly based on experiences and doctors’ observations. Therefore, a demand for a quantitative method is needed to help doctors accurately diagnose the vestibular disease. Moreover, the method is expected to allow monitoring the patient’s situation during the treatment. To response to this demand, this paper applied machine learning technique to build a model to predict a person who has balance disorder. The data is obtained by a self-made device to measure the Center of Gravity (CoG) from people with and without vestibular. Results show that our proposed quantitative method had high accuracy in predicting whether a certain person has balance disorder or not.
