The availability of low-cost portable depth sensor camera brings opportunity to be applied in home-based rehabilitation exercise for stroke and other chronic disease patients. Kinect V2 seemed not feasible to easily track motion in a lying position, while the latest Microsoft Azure Kinect has improved the sensor. This paper experimentally explores the feasibility of Azure Kinect and Kinect V2 for lying position rehabilitation exercises and evaluate the tracking performance by changing the camera viewing angles. Two healthy subjects performed upper and lower limb rehabilitation exercise trial on the bed according to supine position and lateral position. The Kinect sensor was tested at 6 viewing angles in human body coronal plane and sagittal plane. Subject motion data and video were recorded and evaluated by two Kinect camera systems. The results showed that the hardware improvement such as resolution enhancement and the neural network motion tracking algorithm of the Azure Kinect depth camera led to higher performance in lying body motion recognition than Kinect v2 for most of the viewing angles. In conclusion, Azure Kinect could improve the lying position body tracking accuracy and it has great potential in the field of rehabilitation with lying position exercises.