# A Novel Mixed Reality Solution Based on Learning Environment for Sutures in Minor Surgery
## 2 Materials and Methods
### Suture MR Workflow  
We developed our graphical software application in Unity version 2018.1.9f2-MLP using C#. Our solution is clearly divided into three phases as shown in the User Experience (UX) workflow diagram (see Figure 1), where students will be learning practical suture skills while the experience progresses (see Supplementary Materials).  
Figure 1: Suture MRUX workflow. The diagram shows user experience design of Suture MR detailing the selection content of each phase. Phase I (red color) enables needle selection, allowing different needle configurations (indicated by colored arrows), and finally, suture procedure selection; phase II (green color) enables set the workspace; and phase III (yellow color) consists of practicing the interactive activity.  
The first phase consists in the creation of the educational practice case, which allows the desired needle to be related to the selected suture technique. The four techniques developed in Suture MR have been selected according to the criterion of fundamental knowledge. Including more complex techniques is a simple task. The needle types incorporated in our tool follow the commercial standardization by Serag-Wiessner manufacturer [18]. In this first phase, the user selects, through interaction with the panels, the type of procedure to be practiced and the needle configuration, as shown in the red modules of Figure 1.  
Once phase I is completed, a tutorial explains how to use how to use the tools for the selected procedure and how to start the interactive activity. After this tutorial, phase II begins: selection of the workspace. In Mixed Reality, the AR system must comply with the detection of volumes of the 3D elements of the physical space by means of scanning techniques based on point cloud contour detection. This allows the subsequent reconstruction of a digital mesh of the space. From this information, the augmented reality system can calculate the occlusions of the real objects with the digital ones and also position the augmented objects on the surfaces detected in the scan. Usually, this function is provided by the development tool kits of each vendor. For our application, we have used the Magic Leap SDK to implement this specific module (phase II) that shows the user the result of the scanning phase. To allow the user to select the workspace based on whether the observed area is suitable, the classification of each fragment of this scanned surface is calculated internally and labeled as vertical or horizontal, depending on its normal vector. When the user points to a surface with the cursor, the green pointer indicates that the area is suitable for positioning the 3D arm; otherwise, the pointer lights up red. The green-red feedback criterion is based on identifying whether the fragment the user is pointing at, and its neighboring fragments, are horizontal surfaces and the sum of their areas is greater than the area occupied by the 3D arm. As a result, the user visualize, through the Mixed Reality glasses, a realistic 3D arm model on his desk from the real world (see Figure 2).  
At this point, phase III starts and two interactive objects are projected onto the user's hands: the tweezers and the needle holder. In this last phase, the tool must enable realistic user interaction with the virtual arm. To this end, we promote a motor coordination movement based on the activation of the trigger points to complete the suture procedure (see Figure 3).  
Figure 2: Participant testing Suture MR in Magic Leap device. The left image shows the augmented environment displayed on Magic Leap. The right image shows user’s performance during the interactive activity.