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The health status of an elderly person can be identified by examining the additive effects of aging along disease linked to it and can lead to the 'unstable incapacity'. This health status is essentially determined by the apparent decline of independence in Activities of Daily Living (ADLs). Detecting ADLs provide possibilities of improving the home life of elderly people as it can be applied to fall detection systems.. This article looks at Radar images to detect large scale body movements. Using a publicly available Radar spectogram dataset, Deep Learning and Machine Learning techniques are used for image classification of Walking, Sitting, Standing, Picking up Object, Drinking Water and Falling Radar spectograms. The Machine Learning algorithm used were Random Forest, K Nearest Neighbours and Support Vector Machine. The Deep Learning algorithms used in this article were Long Short Term Memory, Bi …