Vision-based fall detection and prevention for the elderly people: A review & ongoing research
Oumaima Guendoul, Ait Abdelali Hamd, Youness Tabii, Oulad Haj Thami Rachid, Omar Bourja
Abstract
Falls are the most leading cause of accidental injury deaths worldwide, therefore, it poses a real challenge for the prevention of life-threatening conditions in geriatrics. The most damaged community is the ever-growing aging population. For this reason, there are considerable demands to distinguish a dangerous posture such as fall in real-time. Here we provide a literature review of conducted work on elderly fall detection and prediction mentioning the main methods to recognize human posture including computer vision-based and wearable sensor-based. We approached these perspectives: sensor fusion, Datasets, approaches proposition. In conclusion, our survey summarizes the progress achieved in the five past years to help the researchers in this field to spot areas where further effort would be beneficial and innovative.