## 6 Field Experiments
### Case Report: Results of Clinical Case 1  
From a clinical perspective, the malocclusion was corrected in both patients. Figures 11 and 12 presents the comparison of wear time recorded by the _SuperPowerMe_ system over a period of approximately nine months. The horizontal axis represents the time frame, marked from 1 week to 9 months, while the vertical axis represents the daily hours of wear time, ranging from 0 to 14 h, which corresponds to the prescribed wear time [18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50]. To fully understand the data visualisation, key components of the graph include: purple vertical bars, which represent daily recorded wear times, indicating variations in the usage of the facemask throughout the therapy period, and coloured horizontal lines,  
Figure 11: Data visualisation of wear time in the first clinical trial reporting the hours of wear time (y-axis) and the month of treatment (x-axis) [30]. which denote the recorded wear time average detected by the sensors integrated in the facemasks (yellow line), the wear time declared in the patient questionnaire (red line), and the benchmark set by the previous study of [PERSON] et al. (2018) (blue line). The first clinical case refers to a 7-year-old female patient, who presented with a Class I dental relationship in the primary mixed dentition and 0 overjet and overbite. Treatments with the personalised facemask spanned from February 2022 to November 2022, totalling 284 days of treatment. Throughout this period, the sensor-embedded personalised facemask successfully recorded 83% of the therapy days. However, missing data were noticeable due to some technical issues orthodontists reported during June and July, particularly with the forehead pads and midline bar, which led to incomplete data capture during those months. These mechanical problems with the facemask contributed to brief interruptions in continuous data collection, highlighting a need for further refinement in the device's durability and fit. When comparing the patient's self-reported wear time with the data collected by the sensors, the results are highly consistent. The patient reported wearing the facemask for an average of 8.5 h per day, while the sensor recorded an average of 8.4 h. The near-identical lines suggest a high degree of reliability in the patient's self-reporting, with any minor discrepancies likely attributable to occasional delays in putting on or removing the mask, or perhaps brief technical lapses in the sensor's ability to capture data. These results offer promising evidence that the facemask, when functioning optimally, provides reliable data on patient adherence, closely mirroring self-reported usage. Regarding the patient's engagement with the game, their behaviour revealed an interesting pattern. The child adopted a strategic approach to gameplay, stockpiling coins and resources to solve multiple quests in a single session rather than spreading her efforts evenly across the therapeutic period. This behaviour suggests a deep engagement with the game mechanics, possibly indicating that the game provided a meaningful distraction or even motivation for wearing the facemask. The patient rated her overall game experience as positive, with particular emphasis on the appeal of the game characters. The design of these characters appeared to be a key factor in maintaining her interest, suggesting that the visual and narrative elements of the game contributed to her adherence to therapy (Table 6). Figure 12: Data visualisation of the second clinical case in terms of wear time reporting the hours of wear time (y-axis) and the month of treatment (x-axis) ([PERSON], 2018). One significant aspect of this case was the gradual increase in the patient's autonomy in wearing the facemask. Initially, during the first week of therapy, the patient required regular parental prompting to wear the device, as she had not yet fully adapted to the routine.