Fall Detection for Elderly People using LiDAR Sensor
A. V. Viswa, V Dharma Pravardhana, Senthil Kumar Thangavel, Gurusamy Jeyakumar · 2024
Understanding the prevalence and severity of accidental falls among the elderly is crucial. Even for those living independently, falls are frequent and can lead to severe injuries, often being a primary cause of elderly mortality. To address this need, the development of a comprehensive platform becomes essential, capable of continuously monitoring individuals’ activity status for timely detection of falls and other unexpected behaviors. Real-time monitoring is vital for providing swift and efficient early warnings during a fall. Conventional methods of monitoring, such as manual surveillance, are resource-intensive and may lack the immediacy required to respond effectively to fall incidents. Therefore, to overcome these limitations, innovative solutions have been introduced. Implementing an automated system can significantly reduce the time and energy expended on monitoring while ensuring a prompt and proactive response to potential fall events. Despite advancements in fall detection research, many existing studies rely on wearable devices primarily within home settings. Extending the scope of these technologies to diverse environments could result in more inclusive and versatile fall detection systems, enhancing elderly safety across various settings. Conventional fall detection systems frequently encounter privacy concerns when employing RGB camera-based monitoring due to their intrusive nature. To tackle this issue, alternative non-intrusive methods such as LiDAR technology have been introduced. LiDAR proves to be effective in detecting falls while also upholding privacy, rendering it a promising option for enhancing geriatric safety.