Assessment of Gait Disorder in Parkinson's Disease

Assessment of Gait Disorder in Parkinson's Disease

Divya Govindaraju (Anna University, India), Gururaj Nagarajan (Birla Institute of Technology and Science, India), and Paramasivam Alagumariappan (B.S. Abdur Rahman Crescent Institute of Science and Technology, India)
DOI: 10.4018/978-1-7998-3441-0.ch032
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Neurological disorders are some of the leading chronic disorders that impose a massive burden on low-income and developing countries. The disability resulting from the neurological disorder increases the severity and costs during the primary healthcare and for entire lifetime. Parkinson's disease (PD) is the second most common chronic neurodegenerative disorder which is slowly progressive with decrease in the motor and non-motor function of the nervous system due to cognitive impairment leading to gait abnormality. PD is most common in the age group of 40-65years leading to increase in gait disorders associated with slowing down of the movement, balance instability, rigidness in the muscles, and difficulty in performing everyday tasks. The assessment of gait plays a significant role in maintaining the balance disorders in Parkinson's disease. In patients with PD, the neurons present in substantia nigra region of the brain get injured, and they progressively decline during their lifetime. Therefore, the patients lose their ability to perform movement and also lose their stability. The symptoms of PD can be monitored and controlled by assessing gait parameters based on gait disorder.
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Parkinson’s disease (PD) is a neurodegenerative disease which mainly affects the human motor system (Rodriguez-Martin, Sama, Perez-Lopez, Catala, Moreno Arostegui & Cabestany, 2017). PD has many symptoms in which the freezing of Gait (FoG) is one among them. In recent years, the classification systems with several classifiers such as Linear Discriminate Analysis, K-nearest neighbour, K-means, Random forest, Naïve Baiyes, Support Vector Machine (SVM), Artificial Neural Network (ANN) etc. are utilized as an automated decision support tools for the early detection of diseases of human body. Eventhough, the Naive Bayes classifier is one of the oldest classifier, it is very simple to implement and needs fewer amounts of training data. This simple and efficient classifier is adopted by several researchers on biomedical and other fields for classification (Sarkar, Goswami, Agarwal & Aktar 2014; Wolfson, Bandyopadhyay, Elidrisi, Vazquez-Benitez, Musgrove, Adomavicius, Johnson & O-Connor 2014;Ahmed, Shahjaman, Rana, Mollah & Haque 2017).

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