## 3 Methodology
### COGNIPLAT Platform and Data Collection  
The data used in this work were collected in the context of COGNIPLAT project (A Gaming PLATform for Restoration of COGNItive Functions of the Elderly People) [28]. A basic aim of this project is to design and implement a serious gaming platform based on rehabilitation methods suggested by the scientific research, so that its employment as part of a therapeutic program, would alleviate MCI symptoms. The COGNIPLAT game platform was built based on a multi-disciplinary approach combining theories of neuropsychology, cognitive linguistics and speech therapy organized in six domains, one diagnostic and five training domains focused on enhancing cognitive functions through different game exercises. In addition, the platform has been designed to automatically adjust the complexity and type of exercises by adapting the cognitive requirements of the games to the characteristics of each patient through an ontology-based knowledge model [29]. In this work data from ten serious games used in the diagnostic mode were collected. Table 2 describes the game types and the associated cognitive functions. Every game played earns points. Different points are awarded for each successful game at a different difficulty level. The calculation of points is based on a formula that combines the level of difficulty and the difference between the completion time of the game and the total time available. The formula for calculating the total score is given below:  
\[\textit{Score}=Difficulty\_Level\_Points\ *\left(1-\frac{\textit{game\ completion\ time}}{\textit{available\ total\ time}}\right) \tag{1}\] \begin{table}
\begin{tabular}{c c c} \hline \hline
**Game Type** & **Description** & **Cognitive Function** \\ \hline Puzzle & Solving a photo puzzle & Attention \\ Maze & Finding the exit from a maze & Visual-motor perception \\ Recall (Anaklisi) & Recall a random sequence of numbers & Short-term memory \\ Calculations & Solving arithmetic crosswords & Working memory \\ Naming & Naming specific types of objects given a set of & Episodic memory \\  & images shown on the screen & \\ Sound Matching & Listening to sounds and selecting the & Acoustic memory \\ Orientation & Placing shuffled images in chronological order & Spatio-temporal orientation \\  & in order to create a brief story & Semantic memory \\ Language & Finding word antonyms/synonyms & Semantic memory \\  & Selecting the right pattern to reasonably & Executive functions \\  & complete the given sequence & Visual memory \\ Memory Cards & Revealing pairs of alike pictures & Visual memory \\ \hline \hline \end{tabular}
\end{table} 
Table 2: COGNIPLAT games used in this study and the corresponding cognitive function targeted. Figure 1: Methodology overview. The design and development of the COGNIPLAT platform was based on the principles of user-centered design in terms of its technological dimension. In recent years there has been a shift in the creation of user-centered systems, especially in the field of health, which while providing care and support, this is done in a way that the patient is not mentally burdened, while entertainment is served. Each game screen was designed in such a way that useful conclusions can be drawn about the performance achieved, such as the speed of initial interaction with the game screen, the speed of successful completion of each task, the number of tasks successfully completed and other relevant statistics that can be collected. Figure 2 provides some examples of COGNIPLAT game screens. The most important feature of the games is the ability to statistically analyze and draw useful conclusions from them. Taking into account the history of player performance and using game performance data, it is possible to observe performance over time and any changes can be noted and analyzed. In addition, the cognitive profile and cognitive status of each user can be monitored through game analysis.