Relational Approach to Knowledge Engineering for POMDP-based Assistance Systems as a Translation of a Psychological Model

Assistive systems for persons with cognitive disabilities (e.g. dementia) are difficult to build due to the wide range of different approaches people can take to accomplishing the same task, and the significant uncertainties that arise from both the unpredictability of client's behaviours and from noise in sensor readings. Partially observable Markov decision process (POMDP) models have been used successfully as the reasoning engine behind such assistive systems for small multi-step tasks such as hand washing. POMDP models are a powerful, yet flexible framework for modelling assistance that can deal with uncertainty and utility. Unfortunately, POMDPs usually require a very labour intensive, manual procedure for their definition and construction. Our previous work has described a knowledge driven method for automatically generating POMDP activity recognition and context sensitive prompting systems for complex tasks. We call the resulting POMDP a SNAP (SyNdetic Assistance Process). The spreadsheet-like result of the analysis does not correspond to the POMDP model directly and the translation to a formal POMDP representation is required. To date, this translation had to be performed manually by a trained POMDP expert. In this paper, we formalise and automate this translation process using a probabilistic relational model (PRM) encoded in a relational database. We demonstrate the method by eliciting three assistance tasks from non-experts. We validate the resulting POMDP models using case-based simulations to show that they are reasonable for the domains. We also show a complete case study of a designer specifying one database, including an evaluation in a real-life experiment with a human actor

Information and communication technology solutions for outdoor navigation in dementia

INTRODUCTION: Information and communication technology (ICT) is potentially mature enough to empower outdoor and social activities in dementia. However, actual ICT-based devices have limited functionality and impact, mainly limited to safety. What is an ideal operational framework to enhance this field to support outdoor and social activities? METHODS: Review of literature and cross-disciplinary expert discussion. RESULTS: A situation-aware ICT requires a flexible fine-tuning by stakeholders of system usability and complexity of function, and of user safety and autonomy. It should operate by artificial intelligence/machine learning and should reflect harmonized stakeholder values, social context, and user residual cognitive functions. ICT services should be proposed at the prodromal stage of dementia and should be carefully validated within the life space of users in terms of quality of life, social activities, and costs. DISCUSSION: The operational framework has the potential to produce ICT and services with high clinical impact but requires substantial investment

Affectively Aligned Cognitive Assistance Using Bayesian Affect Control Theory

Abstract. This paper describes a novel emotionally intelligent cognitive assistant to engage and help older adults with Alzheimer’s disease (AD) to complete activities of daily living (ADL) more independently. Our new system combines two research streams. First, the development of cognitive assistants with artificially intelligent controllers using partially observable Markov decision processes (POMDPs). Second, a model of the dynamics of emotion and identity called Affect Control Theory that arises from the sociological literature on culturally shared sentiments. We present background material on both of these research streams, and then demonstrate a prototype assistive technology that combines the two. We discuss the affective reasoning, the probabilistic and decision-theoretic reasoning, the computer-vision based activity monitoring, the embodied prompting, and we show results in proof-of-concept tests.

LaCasa: Location And Context-Aware Safety Assistant

Abstract—Wandering is a common behavior among people with dementia (PwD). It is also one of the main concerns of caregivers since it can cause the person to get lost and injured. The frequency and manner in which a person wanders is highly influenced by the person’s background and contextual factors specific to the situation. In this paper we investigate some of the properties of wandering behaviours, particularly related to our ability to sense them with mobile devices. We then propose a novel decision-theoretic model that estimates the risk faced by the PwD and decides on the appropriate action to take, such as prompting the PwD or calling the caregiver. The model can be tailored to the user needs (e.g. known locations, level of cognitive decline) and takes into account uncertainty, and contextual information gathered from sensors, such as current location, noise, and proximity to the caregiver. A preliminary version of the system has been instantiated in a wandering assistance application for mobile devices running on an Android platform. I

Energy Efficient Execution of POMDP Policies

Recent advances in planning techniques for partially observable Markov decision processes have focused on online search techniques and offline point-based value iteration. While these techniques allow practitioners to obtain policies for fairly large problems, they assume that a non-negligible amount of computation can be done between each decision point. In contrast, the recent proliferation of mobile and embedded devices has lead to a surge of applications that could benefit from state of the art planning techniques if they can operate under severe constraints on computational resources. To that effect, we describe two techniques to compile policies into controllers that can be executed by a mere table lookup at each decision point. The first approach compiles policies induced by a set of alpha vectors (such as those obtained by point-based techniques) into approximately equivalent controllers, while the second approach performs a simulation to compile arbitrary policies into approximately equivalent controllers. We also describe an approach to compress controllers by removing redundant and dominated nodes, often yielding smaller and yet better controllers. Further compression and higher value can sometimes be obtained by considering stochastic controllers. The compilation and compression techniques are demonstrated on benchmark problems as well as a mobile application to help persons with Alzheimer's to way-find. The battery consumption of several POMDP policies is compared against finite-state controllers learned using methods introduced in this paper. Experiments performed on the Nexus 4 phone show that finite-state controllers are the least battery consuming POMDP policies

Autonomous indoor wayfinding for individuals with cognitive impairments

<p>Abstract</p> <p>Background</p> <p>A challenge to individuals with cognitive impairments in wayfinding is how to remain oriented, recall routines, and travel in unfamiliar areas in a way relying on limited cognitive capacity. While people without disabilities often use maps or written directions as navigation tools or for remaining oriented, this cognitively-impaired population is very sensitive to issues of abstraction (e.g. icons on maps or signage) and presents the designer with a challenge to tailor navigation information specific to each user and context.</p> <p>Methods</p> <p>This paper describes an approach to providing distributed cognition support of travel guidance for persons with cognitive disabilities. A solution is proposed based on passive near-field RFID tags and scanning PDAs. A prototype is built and tested in field experiments with real subjects. The unique strength of the system is the ability to provide unique-to-the-user prompts that are triggered by context. The key to the approach is to spread the context awareness across the system, with the context being flagged by the RFID tags and the appropriate response being evoked by displaying the appropriate path guidance images indexed by the intersection of specific end-user and context ID embedded in RFID tags.</p> <p>Results</p> <p>We found that passive RFIDs generally served as good context for triggering navigation prompts, although individual differences in effectiveness varied. The results of controlled experiments provided more evidence with regard to applicabilities of the proposed autonomous indoor wayfinding method.</p> <p>Conclusions</p> <p>Our findings suggest that the ability to adapt indoor wayfinding devices for appropriate timing of directions and standing orientation will be particularly important.</p

Activity Theory Analysis of Heart Failure Self-Care

The management of chronic health conditions such as heart failure is a complex process emerging from the activity of a network of individuals and artifacts. This article presents an Activity Theory-based secondary analysis of data from a geriatric heart failure management study. Twenty-one patients' interviews and clinic visit observations were analyzed to uncover eight configurations of roles and activities involving patients, clinicians, and others in the sociotechnical network. For each configuration or activity pattern, we identify points of tension and propose guidelines for developing interventions for future computer-supported healthcare systems