Real-time fall detection with ground height awareness using LiDAR and a camera of a mobile device

Falling can lead to bodily harm or even death for humans, so seeking immediate medical attention after a fall is crucial to minimize potential damage. However, it’s important to avoid unnecessary alarms; for instance, falling onto a bed versus falling onto the floor with the same posture and speed can have very different implications.

We have developed a new fall detection system that utilizes LiDAR technology and the camera on a mobile device. LiDAR is used to gather 3D coordinates of the environment and assess the ground’s height based on the lowest point in the scene. Meanwhile, the camera and a pose estimation model capture the 2D coordinates of a person’s skeleton. By combining these data points, we can accurately identify a fall by analyzing the 3D coordinates of the person’s skeleton in relation to the ground’s height.

This advanced system allows us to distinguish whether a person has fallen from an elevated surface to the ground, like a bed or sofa (which generally poses no harm), or on the ground (which may result in injury). The application can also determine if a person remains lying on a bed or sofa, considered a normal case with no alarm, versus lying on the ground, which is an abnormal case and warrants an alarm.

Our study presents the first fall detection method that takes ground height into account, enabling real-time identification of falls using a modern mobile device and sending alerts accordingly with minimal false alarms.