Electronic aids to daily living: be able to do what you want

Purpose. This study explores the experiences of Irish people with high cervical spinal cord injuries living with electronic aids to daily living (EADL) and the meaning attributed to such systems in the context of participation in everyday life. Method. Qualitative methodology using a phenomenological approach was used to explore the phenomenon of living with EADL. Data were collected using four focus groups of users and nonusers of EADL (n = 15). All participants had high cervical spinal cord injuries (C3-5). Groups were video recorded, transcribed verbatim and analysed using descriptive phenomenological analysis. Findings. Findings revealed key elements of the meaning of living with EADL. Two key themes, time alone and changed relationships are described. These contribute to the super ordinate theme of autonomy. Findings suggest that participants perceived improvements in both anticipated and actual lived experiences with EADL. Themes are interrelated and together represent a summary of the experience of living with environmental controls. The themes described are similar to those found in other spinal injury studies relating to quality of life. Conclusions. Findings highlight differences in life experiences for those with and without EADL and provides motivation to address this difference. Such insights are valuable for both users and providers of EADL.

Experiences and desires of people with tetraplegia living with and without electronic aids to daily living: an Irish focus group study

This qualitative descriptive study explores the lived experience for persons with a high cervical spinal cord injury who have Electronic Aids to Daily Living (EADLs), and for persons who have no EADLs. Fifteen people with cervical spinal cord injuries attended four focus groups. Data analysis uncovered a novel framework of several themes that were organised into three categories: experiences, desires and meanings of living with EADL. Users’ and non users’ groups revealed homogenous themes. Experiences and desires are explored further in this paper. Themes within the category of experiences included: EADL devices, supply support and training, abandonment, mouthsticks and powered wheelchairs. Desires included: simple stuff, reliability, aesthetics and voice activation. Findings offer valuable personal insights about life with EADL to be considered by all involved with EADL.

Finding optimal alternatives based on efficient comparative preference inference

Choosing the right or the best option is often a demanding and challenging task for the user (e.g., a customer in an online retailer) when there are many available alternatives. In fact, the user rarely knows which offering will provide the highest value. To reduce the complexity of the choice process, automated recommender systems generate personalized recommendations. These recommendations take into account the preferences collected from the user in an explicit (e.g., letting users express their opinion about items) or implicit (e.g., studying some behavioral features) way. Such systems are widespread; research indicates that they increase the customers' satisfaction and lead to higher sales. Preference handling is one of the core issues in the design of every recommender system. This kind of system often aims at guiding users in a personalized way to interesting or useful options in a large space of possible options. Therefore, it is important for them to catch and model the user's preferences as accurately as possible. In this thesis, we develop a comparative preference-based user model to represent the user's preferences in conversational recommender systems. This type of user model allows the recommender system to capture several preference nuances from the user's feedback. We show that, when applied to conversational recommender systems, the comparative preference-based model is able to guide the user towards the best option while the system is interacting with her. We empirically test and validate the suitability and the practical computational aspects of the comparative preference-based user model and the related preference relations by comparing them to a sum of weights-based user model and the related preference relations. Product configuration, scheduling a meeting and the construction of autonomous agents are among several artificial intelligence tasks that involve a process of constrained optimization, that is, optimization of behavior or options subject to given constraints with regards to a set of preferences. When solving a constrained optimization problem, pruning techniques, such as the branch and bound technique, point at directing the search towards the best assignments, thus allowing the bounding functions to prune more branches in the search tree. Several constrained optimization problems may exhibit dominance relations. These dominance relations can be particularly useful in constrained optimization problems as they can instigate new ways (rules) of pruning non optimal solutions. Such pruning methods can achieve dramatic reductions in the search space while looking for optimal solutions. A number of constrained optimization problems can model the user's preferences using the comparative preferences. In this thesis, we develop a set of pruning rules used in the branch and bound technique to efficiently solve this kind of optimization problem. More specifically, we show how to generate newly defined pruning rules from a dominance algorithm that refers to a set of comparative preferences. These rules include pruning approaches (and combinations of them) which can drastically prune the search space. They mainly reduce the number of (expensive) pairwise comparisons performed during the search while guiding constrained optimization algorithms to find optimal solutions. Our experimental results show that the pruning rules that we have developed and their different combinations have varying impact on the performance of the branch and bound technique.