Elderly People Fall Detection System Using Skeleton Tracking and Recognition

Abstract

The fall detection systems use a variety of technologies like sensors, wearable devices, color camera, thermal camera etc. With the use of Microsoft Kinect camera for non-gaming purposes, depth images have started being utilized for fall detection. Various authors have made an attempt at using Kinect for fall detection in combination with a variety of techniques like ellipse analysis, bounding box analysis etc. However, most of these attempts fail to differentiate between human subjects and other inanimate objects and fail to identify the person who has fallen while assuming that there is only one person who needs to be monitored. This paper proposes a new system that is based on the depth images captured by Microsoft Kinect, skeleton tracking and bounding box analysis. The key novelty of this system is that it wraps the moving object into the bounding box and determines the change of size of the moving object by analysis the motion over the time to distinguish the human moving object and non-human moving object. The system stores the joint measurements of the known people in a database and compares the joint measurements of the detected person with the values in the database to identify the person. The proposed solution provides a significantly higher accuracy rate as compared to the current best solution and especially when the person carrying an object, sweeping the floor, dropping an object and picking an object from the floor.

A Pose Estimation-Based Fall Detection Methodology Using Artificial Intelligence Edge Computing

“…Therefore, in this study, the human body aspect ratio judgment proposed by Ref. [25] is used. By finding the maximum and minimum X-and Y-axis coordinates of 18 human body joint points, the object frame of the human skeleton (bounding box) is obtained, and its aspect ratio Asp is calculated, as shown in (7).…”

Using Low-Resolution Non-Invasive Infrared Sensors to Classify Activities and Falls in Older Adults

“…Some sensors, such as accelerometers, barometers, inertial sensors, and gyroscopes, provide essential data and information for the care of people, especially older adults. Concerning falls, several studies, such as [ 7 , 8 , 9 ], agree on the benefits of using sensors to detect falls. Nevertheless, they also discuss the challenges of using sensors in homes inhabited by older adults.…”