Fall Detection System Using Artificial Neural Network
Anagha Purushothaman, Vineetha K.V., Dhanesh G. Kurup · 2018
Falls are a major concern in health care nowadays. The senior citizens and patients suffering from genetic disorders like muscular dystrophy are more likely to be prone to falls as their muscles weaken over the period of time. Apart from the fall itself, most significant consequences are generally the long lie periods associated with falls. This can cause severe side effects and can be dangerous especially if the person is alone or becomes unconscious after falling. So there is a need for a robust fall detector which is able to accurately detect fall and alert the concerned people for assistance so that the adverse effects of long lie period can be mitigated. This project aims in building an efficient fall detection system using neural network. The key to any fall detection system is the algorithm used. This paper proposes the use of machine learning technique specifically, neural network for the classification of an activity as a fall or non fall event.