ABSTRACT
One of the most pernicious consequences of COVID-19 on society is how it has affected global mental health, creating new problems and aggravating existing ones. Mental health issues and therapy typically take a backseat when the limited resources are equipped for the pandemic. So, it is necessary to track any psychological problems before they get out of our hands. This paper focuses on building a mental health tracker using a machine learning algorithm which mainly concentrates on cognitive mental disorder. It is critical in ensuring that these are caught early and one of the screening tools used for that is MMSE evaluation;it provides a quantitative assessment of cognitive impairment and to log cognitive changes over time. Using K-means clustering algorithm clusters are formed with the possibility of dementia occurrence. © 2022 IEEE.