The interaction between human and machine plays an important role in the design and optimization of human-machine systems. This interaction is characterized by human motion using the technical system. Especially in the field of hand and power tool applications, the motion capture should be performed under the real working condition and without influencing the user. There are already motion tracking systems that allow capturing the motion during the interaction, but there is no mobile motion capture system that allows an individual analysis of the user for biomechanical analysis in the normal work process without influencing him. Therefore, requirements for a motion capture system are derived and a system is presented that meets these requirements. This system consists of two cameras and is based on the pose estimation algorithm OpenPose. The comparison of the presented system and the state-of-the-art system Xsens is performed and based on the measured elbow angle and the wrist position. The results show a very good correspondence between the curve characteristic of the elbow angle and the wrist position of both systems. However, inexplicable values shifting at two different levels still occur, which need to be investigated further. ... mehrOverall, the presented system shows great potential in terms of mobility and flexibility of the presented system with some weaknesses in the data processing and efficiency. By addressing these weaknesses, the presented system can be used in the analysis and optimization of human-machine systems.