## 3 Methods
### The Usage Data Measurement Framework for AAL Systems
#### 3.2.1 Step 1: Usage Data Logging  
The usage data logging step of the framework comprises: (i) the assurance of ethical appropriateness, particularly for ICT-supported solutions for older or vulnerable people; (ii) selection of evaluation objectives and decision on the logging levels; (iii) determination of the logging capacity and bandwidth; (iv) selection of the logging component(s)/data source(s); and (v) implementation of the data logging procedures. Whenever (personal) data of users are logged, legal and ethical assessments are required. National and European regulations aim to improve data protection and user rights [44]. In addition, guidelines for ethical assessments of AAL projects (e.g., References [45; 46; 47]) seek to raise awareness of ethical issues. Ethical considerations usually relate to the type, duration, and frequency of data logging, data storage, and data protection to users' rights to access, rectify, erase, withdraw, and transfer the data. In addition, it is important that researchers only collect as much data as is necessary to answer (pre-defined) research questions. To meet European legal requirements, users must give informed  
Figure 2: Usage data evaluation framework. consent. To ensure the ethical appropriateness of AAL research projects, it is recommended to involve an ethics board or committee to assess the study design, including the aims, materials, and approaches for data collection and methods for the analyses. Evaluation objectives determine the level of usage data collection. If the research focus is on the general use of a system/application, then logging can be restricted to the application level. However, if information about the use of features is needed, then logging at the feature level is required. Considerations of the capacity have to address both the logging duration and the maximum number of users to be logged by the system. For feature-level logging, the logging granularity, i.e., the maximum number of sub-levels per feature, has to be determined. Based on the logging level, the logging capacity and bandwidth can be determined such that the logging component can be selected, configured, and if necessary, integrated into the system of which the usage data should be analyzed. To enable data logging, the logging component has to be configured, and if necessary, integrated into the system of which the usage data will be analyzed. For different logging components, see References [14; 36; 39; 40]. For a multi-component system, one logging component or data source may not be sufficient. Particularly, AAL systems aim to combine different systems and technologies. Depending on the technologies used and the type of the feature, logging a feature's usage may differ on different devices. For example, feature usage on a tablet is not recorded in the same way as, for example, the steps on an activity tracker. While logging of feature usage requires user interaction and user interaction logging, steps are recorded automatically using sensor data without user interaction on the device. Thus, for multi-component systems, where different data sources are needed, a user identifier, such as a universally unique identifier (UUID) [48] connecting the data to the single user, has to be implemented into each of the data sources. The definition of use may depend on the features of a system an on the research questions. For some features, clicking on a button (e.g., to view the weather forecast) may count as \"use.\" Other features may require sophisticated approaches to assess the take-up. This is the case for features that aim to incentivize a user's activities, such as doing exercises. A simple count of clicking on the program will thus not generate meaningful data. In such cases, additional information from time stamps or other components could be useful. In addition, if user profiles are of interest, further information about the characteristics of the users of a system will be needed for the analysis [49], e.g., demographic data, such as gender or age.