Senior Citizen Care using Micro Expression Analysis on Live Elderly Video (MEA-LEV)

The application of Collective Intelligence (CI) conception has produced Senior citizens require treatment and support to lead a healthier life without concern and distress. Old age is a sensible level . Failure to become conscious of the shifting behavioural trends of seniors at home leads to child violence. This work addresses the issues surrounding the lives of older people that find major mental and emotional difficulties much more difficult. Care judgments should be based on a sound and rational appraisal of the needs of each senior in terms of care, not on the ability to be supportive or guilty emotionally motivated.The practical capacities of the elder must be established individually and systematically in order to reach a practical awareness of the types of treatment they may receive. Any capability of the elder which is impaired will require treatment, depending on the vitality of each skill in conducting day-to-day tasks and retaining one's own welfare. If the welfare needs are not fulfilled, the amount of harm the aged person is subjected and the kinds of treatment that will restore the wellbeing of the elderly must be decided. Furthermore, any capacities which will in the near future be affected as a result of the progressive state of an Elder shall be therefore established and included in a care plan.During these inquiries, we report the live video monitoring of elders – a fast and rigorous tool for elderly micro expression recognition that analyses the subtle gestures of different behavioural trends in various areas, using distinct absolute frame variants and the key component analysis classificatory (PCA) in order to predict the most prominent facial and corpuscopal changes.The research indicates that automatic detection of the microexpression produces better (97.34% True Positive and 0.02% False Positive)outcomes by using time and a fast learning algorithm.