# Evaluating the Feasibility of Euler Angles for Bed-Based Patient Movement Monitoring
## 3 Results
The analysis indicates that the rollover movement generates higher dissimilarity values when paired with different types of motion in comparison to others. Figure 7, on the other hand, illustrates the dissimilarity values of varying types of the same body movements when compared against each other. It includes separate dissimilarity matrices for varying rollovers, body drops, rolls to the side, seizures, and head drops. For example, in Figure 7a, the first row represents the varying dissimilarity values when rollover measurement #1 is compared to four other rollover measurements. The purpose of this is  
Figure 5: Euler angles around the frontal axis (i.e., pitch, as demonstrated in Figure 1) as a means of representing different body movements while in bed, contrasting them with the standard motion of rolling over (blue dot-dashed line), i.e., (**a**) rollover vs. drop from the bed, (**b**) rollover vs. roll to the side, (**c**) rollover vs. seizure episode, and (**d**) rollover vs. head drop. to evaluate if similar types of movements show lower dissimilarity values compared to dissimilar types of movements. In other words, it is testing if the dissimilarity values can help distinguish between different movements. The results show relatively low dissimilarity values when comparing similar data sets of shape (same type of movements) and a larger magnitude when compared with different types of movement. In combination, Figures 6 and 7 offer a statistical representation of the variability and differences in movements as detected by their respective Euler angles, suggesting that these differences could be used to identify and categorize different types of patient movements. An example of small dissimilarity values being used as a data set identifier is shown in Figure 8. For instance, when a patient switches from their back to their stomach (known as a rollover), such rollovers have maximal dissimilarity values of 5.9 \(\times\) 10\({}^{-4}\) in comparison with other rollover types; on the contrary, its dissimilarity value for the less similar movement samples has been identified to be at least 0.0145. There is an almost twenty-five-fold difference between these two metrics and this thereby highlights the reliability placed  
Figure 6: The values indicating differences between body movements are obtained through the comparison of each movement with others. The five different types of movements evaluated in this study include rolling over from the back to the stomach (**A**), dropping from bed (**B**), rolling to the side (**C**), experiencing a seizure (**D**), and head drops (**E**). Figure 7: Dissimilarity values of varying body movements in bed when compared against each other, e.g., the first row of figure (**a**) represents the rollover measurement #1 compared to four other rollover measurements. upon these dissimilarity values as markers or defining characteristics that help identify data sets analogous to and consistent with the reference set being utilized for analysis purposes. Nevertheless, the information depicted in Figure 8 only presents a comparison of one rollover movement. In order to ascertain its applicability for various types of rollovers, each distinct movement was assessed against all forms of rollovers, illustrated in Figure 9. The dissimilarity value reaches a maximum of 0.0025 when comparing all rollovers to each other, while the minimum value is 0.01 for all body movements compared with every measured rollover (now just rollover 3 as in Figure 8). This represents a stark fourfold contrast in values that can effectively serve as an identifying factor for movement classification based on dissimilarity values alone. To reiterate, Figures 8 and 9 further delve into the comparison of dissimilarity values when distinguishing body movements based on Euler angles. In Figure 8, the reference bodily motion chosen is rollover 3. The figure displays the dissimilarity values obtained from comparing this reference data set to other similar rollovers, contrasted against dissimilar body movements.