Fall Detection Methods for Elderly People- A Comprehensive Survey

This survey research gives a thorough analysis of sensor technology and picture preprocessing methods for fall detection systems for elderly people. Caretakers face serious health hazards and difficulties when an older person falls. Numerous sensor-based and vision-based solutions have been put forth to deal with this problem. This survey talks about the difficulties with effective implementation of these techniques, such as sensor location, data fusion, and power management. It also examines several pictures' preprocessing methods, including background removal, object detection, tracking, and feature extraction, which are crucial for improving the precision and responsiveness of vision-based systems. This study also examines the benefits and drawbacks of the various sensor technologies used, such as accelerometers, gyroscopes, depth cameras, infrared sensors, pressure mats, and wearables. Important data on elderly falls is also provided to further emphasize how urgent it is to have effective fall detection systems. With the help of improved fall detection systems, this study will serve as a significant resource for researchers and practitioners, leading future developments to increase the safety and well-being of senior people.