अमूर्त

A Review on Parkinson Disease Classifier Using Patient Voice Features

Priyanka Holkar, Payal Gatti, Sonali Meher, Pooja Sable

Parkinson’s disease (PD) known as chronic and progressive movement disorder, means that symptoms continues and becomes worst over time.PD affects on person’s moves, also affects how they speak and write. After Alzheimer’s disease, around whole world 6.3 million people live with Parkinson’s disease which makes it the second most common neurological disorder. The cause of disease is unknown, and also there is presently no cure and no treatment options such as medication and surgery to manage its syndromes. Approximately 90% of PD patients have suffered speech difficultiesi.e., dysphonia which is impaired speech production and dysarthria is referred as speech articulation difficulties. These mobility deficits are difficult to treat with drugs or neurosurgery. Parkinson disease people must visit clinician to track their progressions regularly. It will become simple process to anticipate harshness of disease with the help of voice recording of patients. This can be achieved by using Hoehn Yahr Score and Parkinson disease Rating Scale (PDRS) Score. Combination of machine learning algorithms are used for classification of voice features according to severities of disease.

जर्नल हाइलाइट्स

अंकीय संकेत प्रक्रिया अतुल्यकालिक संकलन अधोचालकसंचालन अनुकूली संकेत संकेत अलग नेटवर्किंग आर्टिफ़िशियल क्लिनिक और इलेक्ट्रिकल में इलेक्ट्रिक ड्राइवर और उत्पाद इलेक्ट्रॉनिक सामग्री इलेक्ट्रॉनिक्स में आर्टिफिशियल ब्यूरो उपग्रह संचार एपीसैन निदान एवं संवेदन प्रणाली नियंत्रण सिद्धांत और सिद्धांत पावर इलेक्ट्रॉनिक कन्वर्टर्स का विश्लेषण बायो इलेक्ट्रॉनिक्स बिजली की गुणवत्ता और आपूर्ति की लागत के आर्थिक मूल्यांकन बेसिक इलेक्ट्रिकल इंजीनियरिंग भार एवं विद्युत पावर प्लांट की विद्युत एवं औषधि उपयोगिताएँ विद्युतचुंबकीय क्षणिक कार्यक्रम (ईएमआई) विद्युतीकरण

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