## 2 Related Works  
In the medical field, VR and mixed reality (MR) are mainly applied in surgical planning and training. Several reviews [1; 2; 3; 4] highlight the current application of VR and MR in surgical training for orthopedic procedures. According to these studies, numerous randomized clinical trials (RCTs) demonstrate the proficiency of innovative virtual techniques in teaching orthopedic surgical skills. In this framework, pilot studies [11; 30] and clinical trials [31] evaluate whether VR or MR improve learning effectiveness for surgical trainees compared to traditional preparatory methods in orthopedic surgery. Innovative surgical simulators are presented in [8; 9; 10; 32], proposing new approaches in surgical navigation, training preparations, and patient-specific modeling. The efficiency of the HoloLens as a suitable device for such applications is highlighted in the previously mentioned studies [4; 8; 9; 10; 11; 20; 32]. For instance, ref. [33] specifically analyzes the use of the HoloLens 2 (HL2) in orthopedic surgery and compares it with the previous version HoloLens 1. Moreover, several studies [33; 34] evaluate and quantify errors committed by the device in positioning and overlapping the virtual object with the real object reproduction. The results of [33] show that the newest model improved the AR projection accuracy by almost 25 percent, while both HoloLens versions yielded a root mean square error (RMSE) below 3 mm. In addition, [PERSON] and colleagues [34] evaluate possible new orthopedic surgical guidelines. In addition, the authors in [6; 20; 21] propose the applications of AR, VR, or MR in pose or posture evaluation and correction. In these studies, tracking algorithms and systems, such as OpenPose and Vuforia, are used to recognize the position of the subject and to identify the posture accordingly. The aim is to provide support in the sport and physiotherapy fields and the diagnosis of orthopedic disease. [PERSON] [35] was the first to introduce martial arts in an AR game where the player has to fight virtual enemies. In [29], [PERSON] et al. composed an AR martial arts system using deep learning based on real-time human pose forecasting. An external RGB camera was used to capture the motion of the trainer. The student wore a VR-Head Mounted Display (HMD) and could see the results directly on the screen. Moreover, [PERSON] et al. [36] focused their work on the construction and visualization of the posture-based graph that focuses on the standard postures for launching and ending actions. They propose two numerical indices, the Connectivity Index and the Action Strategy Index, to measure skill level and the strengths and weaknesses of the boxers. In a physiotherapeutic application, [PERSON] and co-workers [6] developed an AR tool to accurately overlap anatomical structures on the subject in motion on the HoloLens device using the external tracking system VICON. In [6], they present the first real-time bone mapping system of a moving subject. The VICON represents the gold standard of tracking and gait analysis systems but realistically is not usable in the everyday medical field. A markerless and dynamic system, such as the Microsoft Kinect, although less accurate, can be considered a viable technology to introduce to clinics and hospitals [37; 38; 39; 40; 41]. Certain precautions are necessary, such as designing a suitable joint model to correct device error. The last version of the Microsoft Kinect devices, the Azure Kinect, has been validated by several studies [42; 43; 44]. In [42], the Azure Kinect showed a significantly higher accuracy of the spatial gait parameters than the previous version. Results provided by [43] confirm the officially stated values of standard deviation and distance error, i.e., std dev \(\leq\) 17 mm and distance error \(>\) 11 mm + 0.1% of distance without multi-path interference. However, this study suggests a warmup of the device of 40 min before acquisition to obtain stable results.