Open AccessA Heuristic Model for Predicting Human Fall Detection using Machine Learning Techniques
Author(s) -
Mohammed Inayathulla,
Prabha Kiran,
Mulyana Sri,
M. Deepika
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3180.079220
Subject(s) - artificial intelligence , computer science , machine learning , classifier (uml) , heuristic , human health , medicine , environmental health
It is very obvious that human fall due to unconsciousness is a very common health problem in every human being. With the evolution of many smart health devices, we should contribute the technological advancement of machine learning into it. Different techniques are already used in order to detect human fall detection in human beings. In this paper we have studied the patterns of falling of human through the fall detection dataset while this human was performing various motions. By understanding all these we have generated the prediction protocol which estimates the fall of a person using fall detection dataset. Machine Learning classifiers were used to predict the human fall and a comparative study of various algorithms used was developed to find out the best classifier.