## 3 Novel Human Machine Team Design
### Human-in-the-Loop (HIL) Simulation Method
#### 3.3.2 Experiment Case 2: Medic Treating Patient
A compensation sum of fifteen dollars, although reasonably not a large amount, was paid to the participants as part of compensation for participation. Due to the candidates' voluntary participation and the absence of an English proficiency test, no screening test was necessary before participation. All the participants were briefed with the help of video aids about testing scenarios prior to the experiments. The briefing included the treatment process and VBSA usage in no more than five minutes to paint an equal mental picture of the situation for all participants. 5. Experimental Procedure: The experiment conducted in this study is similar to that of Case 1 and comprises of two trials. Each trial lasted from 60 to 120 s. The scenario comprised of 17 execution steps and began with a hemorrhage treatment performed on a complete manikin followed by diagnosis of three different parameters of a patient's condition, such as breathing airways, respiration rate, and capillary refill, and it concluded with the gathering of patient background information. The experiment was conducted in quiet rooms (e.g., briefing, testing, and survey) under total isolation, and any chance of contact with fellow participants was strictly prohibited in order to avoid human factor bias. The process was as follows: 1. Initially, each and every participant was briefed about the scenario individually with the help of a two minute video. The task entailed hemorrhage treatment and patient diagnosis process-flow with the help of a VBSA. Right after the briefing, the participants were taken to a testing room for task execution. 2. During the testing period, the participants were asked to execute total task execution steps on the patient manikin model, which were made available on a dashboard screen. 3. Participants began the task with massive hemorrhage treatment similar to that of Case Study 1, then checked a patient's airways and cleared any obstruction by applying chest compression and rescue breath. 4. Later, patient respiration diagnosis was performed, and the patient was placed in a tripod position in order to relieve any chronic obstructive pulmonary disease (COPD) detected. 5. Adding to that, a capillary refill was made by examining physical appearance (e.g., skin color, nail press). From there, the pulse rate was immediately evaluated. 6. Finally, a patient's background information, such as weight, age, gender, and allergies, was gathered. The examiner recorded the testing period as per standard data collection guidelines. 7. After the testing session, the participant proceeded to a survey room for user validation. This consisted of a post-test questionnaire related to user task experience. The data collected in the due process, illustrated in the section below, was then put to extensive scrutiny to extract results. VBSA Web interface mentioned in Section 3.1 plays a key role. 6. Data Collection: The experimental data was collected from time-stamped video recordings logged during the testing scenario and user validation processes conducted after the testing scenario. A real-time video recording was made by an external observer who was responsible for capturing every detail of the task scenario such as VBSA tracking performance, time of execution, errors in executing task sequence steps, and rate of response. The user validation process involved a post-test questionnaire to extract a user's feedback related to task experience. Metrics were collected in this study and were submitted for further subjective analysis. The rate of response, number of interventions, and tracking performance of VBSA were also considered as part of team performance evaluation. 7. Data Analysis: As mentioned above, the objective behind this experiment is to assess the performance of an HMT. In this regard, emphasis was placed on performance assessment of the participant and the VBSA, both individually and as a team. This was achieved from the metrics recorded during the testing scenario. The performance score was calculated from metrics using Equation (1).