Isometric Contraction ankle joint in Cerebral Palsy using Naive Bayes

Muhaimin Hasanudin, Yudo Devianto, Wawan Gunawan, Saruni Dwiasnati, Ifan Prihandi

Abstract


Cerebral palsy is an abnormal brain development or brain damage that affects the sufferer's ability to move and maintain their balance and posture. Spastic Cerebral Palsy is a type of Cerebral Palsy that has brain damage and muscle stiffness. These muscles become stiff because the message to the muscles is delivered incorrectly by the damaged part of the brain. The purpose of this study is to classify isometric contractions in Spastic Cerebral Palsy (SCP) children aged 5-15 years with GMFCS levels at levels 1 and 2 using the Naive Bayes Algorithm while the dataset used is open public, namely Mendeley Data Repository, there are 24 attributes used to classify isometric contractions of the ankle joint in SCP children. Existing data is divided into training data and test data based on hold out validation. Based on the classification results, Naive Bayes with a training and test data ratio of 1:1 produced the highest accuracy of 84%.

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References


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