Healthier Aging: A Systematic Review of Different Fall Detection Techniques in Home and Outdoor Environments
Tamonash Bhattacharyya, Prasun Ghosal · 2023
Among several disciplines, IoT has provided a promising prospect for Smart Healthcare and has seamlessly paved the way for various modern-day healthcare systems. A significant part of modern-day healthcare revolves around providing the most optimum and cost-effective healthcare services to the elderly, who need a round-the-day monitoring system to provide them with a safe and quality living experience. In this scenario, we concentrate on one of the most crucial causes of accidental injuries: falls. In this paper, we provide a systematic review of the various Fall Detection Systems currently in use or under research, exploring the various technologies that have contributed to their development and hinting at the various drawbacks of each of those systems. We have categorized the various systems under two major categories: Systems for Home Environments and Systems for Outdoor Environments. The various Fall detection systems developed specifically for Home environments employ sensors ranging from wearable sensors such as accelerometers and pulse rate sensors to using RGB-D Cameras to monitor body postures. Some fall detection systems have implemented a threshold-based detection model where the magnitude of the various features considered exceeds a specific limit; the estimator indicates a fall. On the other hand, in many systems, machine learning algorithms such as Random Forest Classifiers and Neural Network models have been implemented to distinguish fall events from non-fall events. This paper explores all such systems, discussing in a broader sense how each has been implemented and what issues have transpired from some of their implementations. This puts into perspective the pathways into which fall detection systems have made significant progress and provides the scope for future research in this field that can bridge the lacunas and pave the way for a more accurate and reliable fall detection system for the healthier aging of tomorrow.