## 2 Materials and Methods  
The prototype of a virtual mouse application controlled with hand gestures captured from a Kinect-based sensor was developed for surgical purposes. The application can handle the majority of Windows applications. The Kinect device was used as a motion sensor. Microsoft launched the device in 2010 with gaming as its primary implementation. However, it should be mentioned that non-gaming applications and Kinect for Windows appeared around 2011 and began to be used in medicine [22; 23; 24], frequently in rehabilitation [25; 26; 27; 28; 29], posture assessment [30; 31], and gait analysis [32; 33; 34]. The Kinect is no longer produced in its former form. In 2020, Microsoft released a continuation of the technology as Azure Kinect by integrating with the Microsoft Azure cloud computing platform, enabling the compatibility of the solution [35; 36; 37]. It was devoted to recognizing body gestures and serves as a game controller. The device has a high-resolution color camera and a depth sensor with a lower resolution. It allows for capturing RGBD (RGB + depth) images at a frequency of 30 frames per second. Four microphones have a noise-filtering function. Preliminary tests facilitated the choice of the specific hand gestures used in the Ortho_Kinect_OR application for some Kinect sensor gaming experiences and were selected by the authors considering the circumstances and specific environment of the OR. Gesture Recognition Algorithms (GRA) enabled control based on three modes: Mode 1 (Figure 1a) is created by combining a gesture with two fingers raised and simulating a mouse button. Moving the cursor was like moving the operator's hand; finger movements allowed the operator to imitate a raised click. Mode 2 (Figure 1b) simulates the action of the mouse rollers by pushing the open hand up and down, which allows for fast scrolling. Mode 3 (Figure 1c), making a fist, was used by moving the cursor while holding the left mouse button. The above approach allowed objects to be rotated and moved in many applications for graphics. The back-and-forth movements imitate the action of a roller. It is possible to recognize these gestures when using a computer, browsing the web, and using various applications. The functionality described above was implemented in C++ and installed as a virtual mouse controller on the OR PACS station. The OR PACS station has an easy-to-disinfect medical keyboard, an integrated touchpad, and an antibacterial coating. After placing the switchboard in it, the keyboard served as the basis for the Kinect. Kinect is connected using one of the USB connectors. Testing was conducted on the OR-PACS station using PACS software (Philips IntelliSpace Release 3.2.SP1) used routinely at the facility to view DICOM files. This setup allowed the user to evaluate the usability and user-friendliness of such a system. Field testing and feasibility studies aimed to provide an early version of the application to a small sample of the target audience. By testing the application in a \"real\" environment, app developers can gather valuable information that will help them improve survey items. The feasibility study aimed to objectively and rationally reveal the strengths and weaknesses of the developed solution. Generally, feasibility studies precede the project's technical development and final implementation. A feasibility study evaluates the project's potential for success. The authors conducted the study as objectively and impartially as possible. The study was conducted from 1 October 2014 to 30 December 2014. Participants were first familiarized with the procedure and purpose of the study. After formal acceptance, they were prepared to enter the OR to perform experimental tests. The recruited orthopedic surgeons invited to participate in the Center of Excellence \"TeleOrto\" field tests presented different experience levels and demographic characteristics. Participants were given a few minutes of instruction (five minutes per person) to use the gesture learning program.