Microsoft released the first version of its Kinect camera in 2010 as a gaming controller for the Xbox gaming console. It can track certain joint positions of users in 3D. It combines an RGB camera with a 3D depth sensor. Since the second camera generation, the Time-of-Flight (ToF) principle has been used for depth estimation. This method estimates the depth by emitting IR-light into the scene and measuring the time until it gets reflected and returns to the sensor. For 3D motion tracking, Kinect v2 used randomized decision forests to estimate the joint locations, as described in . In 2019, a new Kinect generation, Azure Kinect, was released where the focus is shifting away from games towards industrial applications. The skeleton tracking algorithm utilizes deep learning with Convolutional Neural Networks (CNN) to estimate the human poses. The research community has used the Kinect camera for medical and biomedical applications and analysis for many years.
In this project, we utilized the latest Microsoft Azure Kinect camera for gait analysis. Gait analysis is an essential tool for the early detection of neurological diseases and assessing the risk of falling in elderly people. More specifically, we evaluated the pose tracking performance of the Azure Kinect camera compared to its predecessor Kinect v2 in treadmill walking. We have used a Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model as the gold standard. Five young and healthy subjects walked on a treadmill at three different velocities. Data were recorded simultaneously with all three camera systems. To compare the spatial agreement of joint locations, we have developed an external camera calibration to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. Specific gait parameters were calculated for all three camera systems, including step length, step time, step width, and stride time. The results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2. At the same time, no significant differences were found between the temporal parameters. The results of this study were published in the MDPI sensors journal.