Gait Dataset for Knee Osteoarthritis and Parkinson's Disease Analysis With Severity Levels
Computer-vision seems to be the most focused area in order to perform efficient diagnosis in clinical applications. The direct connection among human brain and the musculoskeletal system directed our effort towards the analysis of such diseases that have the significant impact on a person's gait such as knee osteoarthritis (KOA) and Parkinson's Disease (PD). Previous research on these diseases based on gait involves certain drawbacks including unavailability of a vision-based public and authenticated dataset. Thus, we created and presented a new dataset namely "KOA-PD-NM" while keeping various factors into consideration (e.g. age, gender, disease severity levels, etc.). This dataset involves both normal/healthy (NM) and abnormal (KOA, PD) subjects and don't allow the analysis of only lower body (limbs) but the upper body (arm, posture) movement too. The key aim of this dataset is to analyze the deviations among patient's and normal's gait. The construction of this dataset will surely help the researchers and the society towards this area for prediction of diseases with different stages and the development of better techniques and strategies.