Tailoring assistive systems for guiding and monitoring an individual in daily living activities is a complex task. This paper presents ALI, an assistive system combining a formal possibilistic argumentation system and an informal model of human activity: the Cultural-Historic Activity Theory, facilitating the delivery of tailored advices to a human actor. We follow an activity-centric approach, taking into consideration the human’s motives, goals and prioritized actions. ALI tracks a person in order to I) determine what activities were performed over a period of time (activity recognition tracking), and II) send personalized notifications suggesting the most suitable activities to perform (decision-making monitoring). The ALI system was evaluated in a formative pilot study related to promote social activities and physical exercise.
The main purpose of assistive technology is to support an individual's daily activities, in order to increase ability, autonomy, relatedness and quality of life. The aim for the work presented in this article is to develop automated methods to tailor the behavior of the assistive technology for the purpose to provide just-in-time, adaptive interventions targeting multiple domains. This requires methods for representing and updating the user model, including goals, preferences, abilities, activity and its situation. We focus the assessment and intervention tasks typically performed by therapists and provide knowledge-based technology for supporting the process. A formative evaluation study was conducted as a part of a participatory action research process, involving two rehabilitation experts, two young individuals and one senior individual as end-user participants, in addition to knowledge engineers. The main contribution of this work is a theory-based method for assessing the individual's goals, preferences, abilities and motives, which is used for building a holistic user model. The user model is continuously updated and functions as the base for tailoring the system's assistive behavior during intervention and follow-up.
1 September 2015 in International Journal of Approximate Reasoning