Smart home based ambient assisted living: Recognition of anomaly in the activity of daily living for an elderly living alone

Abstract

Many people with incapacities can continue lives in their existing home with the application of an assistive informatics and healthcare monitoring. Elderly's ability to perform daily activities presents the elderly's wellness. Investigation of human activities for extracting health and well-being statistics is one of the present challenges given the Smart Aging. The existing research works are mostly focusing on offline monitoring and do not give significance to real-time monitoring and forecasting. This paper aims to apply lifestyle monitoring and forecasting in real time in ambient assisted living (AAL) system with diagnosing the conduct and distinguishing the variation from the norm with the slightest conceivable fake alert. Anomaly forecasting model based on inactivity and activity of period of the different ADL is formulated. The present study demonstrates the novel approach for forecasting of wellness anomaly related to the activity of daily living (ADL). The significant correlation between lifestyle and health status is established. Through the present research forecasting of lifestyle would facilitate remote physician/caregiver to insight symptom of the disease and provide health improvement advises to the resident. Moreover, if it is a life-threatening degradation in wellness index than appropriate service provider would be informed directly.