![A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbmdSIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--c3d6d1b143e909db45a51a2ea295eb9165b37df2/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--33b2b080106a274a4ca568f8742d366d42f20c14/Figure2.png)
Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.
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