We present an approach for personalizing nonpharmacological interventions for people with dementia (PwD) using ontologies. We conducted two case studies to derive an ontological model to personalize the planning and execution of interventions to address problematic behaviors. The paper describes how the ontology was derived, and illustrates how it is used to tailor an ambient-assisted intervention system (AAIS) at two stages: first, to decide on the services that the AAIS will offer the PwD, and then to adapt these services at runtime using contextual information. The results of a deployment of an AAIS during 2 months in the home of a PwD, indicate that the AAIS successfully addressed some of the problematic behaviors exhibited by the PwD, helping to reduce the burden of the caregiver.

The cognitive deficits in persons with dementia (PwD) can produce significant functional impairment from early stages. Although memory decline is most prominent, impairments in attention, orientation, language, reasoning, and executive functioning are also common. Dementia is also characterized by changes in personality and behavioral functioning that can be very challenging for caregivers and patients. This paper presents results on the use and adoption of an assisted cognition system to support occupational therapy to address psychological and behavioral symptoms of dementia. During 16 weeks, we conducted an in situ evaluation with two caregiver-PwD dyads to assess the adoption and effectiveness of the system to ameliorate challenging behaviors and reducing caregiver burden. Evaluation results indicate that intervention personalization and a touch-based interface encouraged the adoption of the system, helping reduce challenging behaviors in PwD and caregiver burden.

The care for patients with Alzheimer's Disease (AD) imposes significant burden on care providers. Often the primary care giver is an elder with health issues of her own. Repetitive questioning is one of the behaviors that cause more stress on caregivers. We present the results of a usability study of an Ambient Augmented Memory System aimed at assisting patients with early AD and their care providers deal with this behavior. The system uses digital cue cards in a mobile phone and a digital memory board at home. An important concern in the design, and the focus of the evaluation study is not to create more stress on the care provider in operating the system, an important challenge considering that they often have no previous computer usage experience.

Mobile phones include a variety of sensors that can be used to develop context-aware applications and gather data about the user's behavior, including the places he visits, his level of activity and how frequently and with whom he socializes. The collection and analysis of these data has been the focus of recent attention in ubiquitous computing, giving rise to the field known as mobile sensing. In this work, we present a collaborative extension to InCense, a toolkit to facilitate behavioral data gathering from populations of mobile phone users.