Table 1: Key findings.

System Suggested Year Computer Vision technology Machine Learning Technique The Abnormality Identified Using the Gait Analysis Reference
Automatic Health Problem Detection 2018 Videos captured using digital cameras DNN Parkinson’s disease
Pose Stroke
orthopedic problems		 [2]
A vision-based proposal for classification of normal and abnormal gait 2016 RGB Camera KNN and SVM Dementia
frailty		 [3]
Computer Vision-Based Gait Analysis 2018 Smart Phone KNN Senility
Frailty		 [3]
Extracting Body Landmarks from Videos 2019 Videos Suggested future work for classification or regression algorithms Parkinson disease [4]
System to support the Discrimination of Neuro-degenerative Diseases 2009 Videos SVM, Random Forest, and KStar Amyotrophic lateral sclerosis, Parkinson's disease, and Huntington's disease [5]

Several measures were identified in the gait analysis to study the abnormality of the patients, some of which are in Table 2.