PERFORMANCE ANALYSIS OF VARIOUS MACHINE LEARNING ALGORITHMS FOR FALL DETECTION-A SURVEY
European Journal of Molecular & Clinical Medicine,
2023, Volume 10, Issue 2, Pages 613-624
Abstract
Improper activities appear nowadays for the human (i.e.) falling without aware, and numerous techniques had been developed to reduce them. In this essay, critically analysis of the various proposed methodologies by comparing their strength and their weakness. The complexity and diversity of actions make it difficult to recognise them. The conventional (CCTV) method is ineffective and expensive for monitoring patient activities by using sensor based is also difficult due to drained battery life. So we need real time system for activity recognition with more efficiency and accuracy to avoid people from morality problems or it may lead to causes to major injuries. By comparing various algorithm Support vector machine (SVM) is a discriminative classifier belonging to supervised learning. Recurrent neural network (RNN) is one of the concepts in deep neural network. The main intention of the RNN is to minimize the preprocessing. This application will seem like visual imagery analysis. The convolutional neural network (CNN) it is more cost expensive compared wearable and ambience based
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