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in most testbeds, they normally produce a non-negligible number of false positive (false alarms) and false negatives (unnoticed falls). As aforementioned, ML and deep learning methods usually exhibit a much greater adaptability to identify human dynamics40. However,...
"Shortly after, an elderly family friend fell in her kitchen and she lay on the floor for two hours until her husband came home. "This cannot be the way things go, this needs to change." He said existing personal alarms were 'old technology' and don't use many of the advances in el...
Furthermore, a slight improvement should be made to reduce the number of false alarms. Keywords: fall detection; wearable sensors; elderly people monitoring 1. Introduction Fall Detection (FD) is a very active research area, with many applications in health care, work safety, etc. [1]. Even...
Human falls, especially for elderly people, can cause serious injuries that might lead to permanent disability. Approximately 20–30% of the aged people in the United States who experienced fall accidents suffer from head trauma, injuries, or bruises. Fall detection is becoming an important public...
Most of the recent techniques produce a lot of false alarms, as it is hard to train them to cover a wide range of fall situations. Hence, this paper aims to detect the exact fall frame in a video sequence, as such it will not be dependent on the whole clip of the video sequence. ...
Fall Detection Systems (FDSs) based on wearable technologies have gained much research attention in recent years. Due to the networking and computing capabilities of smartphones, these widespread personal devices have been proposed to deploy cost-effective wearable systems intended for automatic fall dete...