Final report Synopsis: Neurodegenerative diseases such as Parkinsons disease, Huntington disease, and Amyotrophic Lateral Sclerosis are caused due to neuro-degeneration process.
Symptoms of each condition are almost similar and misleading, so accurate identification of particular disease is significantly difficult. As neurodegenerative diseases are life-threatening, diagnosis is crucial in order to provide proper treatment on time for reduction of symptoms.
Neurodegenerative disease often affects gait and mobility. Therefore, gait recognition is a proven diagnostic method for accurate identification of neurodegenerative diseases.
Analysis of gait signal recorded from neurodegenerative patients using novel machine learning techniques may speed up the accurate detection and classification of type of neurodegenerative diseases (Parkinsons disease, Huntington disease, and Amyotrophic Lateral Sclerosis).
Objectives:
A student attempting this project will be developing algorithm for the detection of neurodegenerative diseases from gait signal. In addition, algorithm should be able to do the classification of different types of neurodegenerative diseases present (Parkinsons disease, Huntington disease, and Amyotrophic Lateral Sclerosis).
Deliverables: Machine learning algorithm for the detection of Neurodegenerative diseases from the gait analysis. Algorithm for the classification of type of Neurodegenerative diseases (Parkinsons disease, Huntington disease, and Amyotrophic Lateral Sclerosis)
