# Pattern Recognition in Older Adults' Activities of Daily Living
## 3 Materials and Methods
### Pattern Recognition
In the kitchen compartment (Figure 14), we can identify periods of movement, namely between 9 am and 10 am, 12 pm and 1 pm, and 8 pm and 9 pm. As expected in the bathroom, no movements are identified during most of the day, as shown in Figure 15. The 75 th percentile reveals a more significant presence in the early morning between 8 am and 9 am, in the early afternoon after lunch around 2 pm, and at the end of the day between 10 pm and 11 pm. Figure 14: The 25 th and 75 th percentile values per hour in the kitchen compartment. Figure 13: Total occurrences per hour in the none or outside scenarios. As for the bedroom compartment, Figure 16 shows that the 25 th and 75 th percentiles in certain parts of the day are very constant and almost always equivalent throughout the day. Thus, analyzing the percentiles, it can be concluded that they reveal a more significant presence between 12 am and 9 am, and also, from 11 pm onward, this presence begins to increase. This is because the person usually sleeps during this period. In the living room compartment, the presence of users between 2 pm and 4 pm is once again validated through Figure 17. During this period, the number of records is constant. Furthermore, between 10 am and 11 am, and 10 pm and 11 pm, there is also a significant presence in this compartment. In the none or outside area, by viewing the graph in Figure 18, it can be seen that between 4 pm and 6 pm, there is a greater possibility of the person being away from home. In addition, other time intervals may have more significant potential, but this may have to do with sensor failures when collecting the data sent by the beacons in each compartment or the person being out of the house. Figure 10.0 The 25 th and 75 th percentile values per hour in the bedroom compartment. Figure 10.1 The 25 th and 75 th percentile values per hour in the bathroom compartment. ### Occupation Probability

Calculating the probability of an inhabitant's presence in a specific compartment was an additional mechanism to study movement patterns and occupancy within the living environment. This approach provided valuable insights into the likelihood of finding an individual in a particular compartment during a given hour. To assess the compartment's occupancy probability hour by hour, the average for each compartment is calculated based on the occurrences, and the probability is calculated by dividing the average number of occurrences for each compartment by the number of days, hour by hour. The calculation of compartment occupancy probabilities, as outlined in Section 3.9, contributed to the broader analysis of daily living patterns and behavior. It complemented detecting outliers and patterns identified through other mechanisms, providing a comprehensive view of the inhabitants' activities and movements within the live environment. After calculating the probability, hour by hour, the similarity between the occurrence chart (Figure 9) and the probability chart (Figure 19) was again verified. According to the probability graph in the kitchen compartment, it is more likely that the person is in this compartment due to breakfast, lunch, and dinner. It can be seen that the intervals are between 10 am and 11 am, 12 pm and 1 pm, and 8 pm and 9 pm, respectively. Figure 10.2 The 25 th and 75 th percentile values per hour in the living room compartment. Figure 10.3 The 25 th and 75 th percentile values per hour in none or outside. The bathroom compartment does not have very high values about the probability of presence, essentially justified by the purpose of this compartment and the type of short-term activities that take place here, verified through Figure 10.4 Even so, the highest values observed between 9 am and 10 am and 10 pm and 11 pm agree with the patterns previously identified in Figures 10 and 15. In the bedroom compartment, the probability graph of Figure 21 shows a very well-defined probability of being in the bedroom between 12 and 9 am. In addition, from 11 pm onward, the likelihood of being in the room increases.