Adaptation of Augmentative and Alternative Communicators through the Study of Interactions with High-Tech Solution Users  
[PERSON]  
1 atanTTic, Information Technologies Group, Telecommunication Engineering School, University of Vigo, Campus, 36310 Vigo, Spain; kikebgt.u.vigo.es (E.C.-M.); [EMAIL_ADDRESS] (C.L.-B. ); [EMAIL_ADDRESS] (F.d.A.-P)  
2 Regional Ministry of Culture, Education, Vocational Training and University, Xunta de Galicia, San Caetano s/n, 15781 Santiago de Compostela, Spain; fmgdoval@edu. differs from studies that directly evaluate user experiences via questionnaires, a matter which has already been proven positive for similar applications [4; 5; 6]. However, we value the significance of the user experience, as our particular app is endorsed by more than 50,000 downloads and plenty of positive feedback from users. This novel study of usage patterns offers hints on how to best adapt applications to the needs of end users who require accessible solutions in their daily interactions by using data analysis and Artificial Intelligence (AI). Therefore, the main objective of this research is to shed light on everyday habits of AAC application users by studying how they interact with a high-tech AAC solution. This can provide insights into how to offer better tailoring to their daily needs and a better and more profound comprehension of the intentions and purposes they attach to these applications. With these hints, we expect not only to foster the use of these AAC solutions but also to offer a better user experience. This will inform future developments in this area. When reviewing previous works on AAC strategies, relevant research highlights that it is possible to classify them according to the following three main characteristics: purpose, autonomy, and use of technology [7]. We drafted this analysis of related works using a hierarchical vision to contextualize the application design that led to our study. The purpose of AAC strategies depends on their desired effect on the preserved abilities of the user. Taking that into account, we can distinguish between rehabilitation and habilitation as follows:  
* Rehabilitating solutions help users in the recovery of their communication capabilities [8; 9]. * Habilitating solutions assist users in acquiring new communicative competencies [10]. Regarding autonomy, the literature defines a classification regarding the involvement of external assistance in AAC strategies. Figure 1 contains a graphic explaining the complete hierarchy of solutions in terms of autonomy. Thus, the more abstract levels that group them are unaided and aided solutions:. Figure 1: Hierarchy of AAC solutions. * Unaided solutions include a wide variety of techniques that only depend on the user [11; 12]. They usually involve symbols, sign language [13], or Enhanced Natural Gestures (ENG) [14]. * Aided solutions are strategies that require external devices or assistance during the communication process [3; 15]. These solutions can be classified into low-technology and high-technology approaches. * Low-tech solutions include non-electronic strategies such as the Picture Exchange Communication System (PECS) [16] or alphabet and symbol boards [17; 18]. * High-tech solutions refer to any computer-based strategy [2; 19], including mobile applications [20; 21; 22; 23], artificial intelligence applications [24], and other technologies, for example, augmented reality [25]. Finally, it is important to add that high-tech solutions present multiple means of interaction depending on the patient's needs [26]. * Eye tracking: Scanning of eye movements and their position relative to a digital display [27; 28]. * Touch displays: This is the most used input method nowadays. It requires the user to interact physically with a touch screen [20; 21; 22; 23]. * Muscular activity recognition: Specific devices that capture voluntary or involuntary body actions.