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

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

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

An Assistive Handwashing System with Emotional Intelligence

Whether emotional intelligence (or, affective reasoning) is included can influence the effectiveness of a cognitive assistive system. This thesis presents a novel emotionally intelligent hand-washing assistant that aims to help older adults with Alzheimer's disease complete hand-washing tasks more independently. The thesis reviews previous works in the development of cognitive assistants and in the study of emotional intelligence, and then designs a hand-washing system prototype that combines the two research streams. The difficulties in designing such a system, including probabilistic and decision-theoretic reasoning of the user's functional and emotional states, computer-vision based activity monitoring and affective recognition, and embodied prompting are discussed. Designing the hand-washing system as an integration of independent components, the thesis also discusses coordination between the components. The thesis implements the system in the end, and shows by preliminary tests in laboratory settings that the system implemented (1) runs in real-time from the perspective of the user group, (2) is able to provide a level of functional assistance, (3) produces system prompts that have encoded to some extent the emotional state of its user. The preliminary tests also indicated that a user with emotions with high potency levels (and high activity levels) is more likely to receive system prompts with low potency levels (and high activity levels). This thesis is one of the exploratory works in the area of integrating emotional intelligence with cognitive intelligent assistive systems. It provides a solution to fitting emotional intelligence in a functional system, as well as points out directions for future improvements. The framework designed in this thesis is portable and extensible, and can be generalized to be used in other applications

NFC based provisioning of instructional videos to assist with instrumental activities of daily living

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Existing assistive living and prompting based solutions have adopted a relatively complex approach to supporting individuals. These solutions have involved sensor based monitoring, activity recognition and assistance provisioning. Traditionally they have suffered from a number of issues rooted in scalability and performance levels associated with the activity recognition process. This paper introduces a simplistic approach to assistive living within a user's residence through the use of NFC tags and smart devices. The core concept of this approach is presented and is subsequently placed within the context of related work. A description of the architecture is provided and results following technical evaluation of the first system prototype are discussed

When technology cares for people with dementia:A critical review using neuropsychological rehabilitation as a conceptual framework

Clinicians and researchers have become increasingly interested in the potential of technology in assisting persons with dementia (PwD). However, several issues have emerged in relation to how studies have conceptualized who the main technology user is (PwD/carer), how technology is used (as compensatory, environment modification, monitoring or retraining tool), why it is used (i.e., what impairments and/or disabilities are supported) and what variables have been considered as relevant to support engagement with technology. In this review we adopted a Neuropsychological Rehabilitation perspective to analyse 253 studies reporting on technological solutions for PwD. We analysed purposes/uses, supported impairments and disabilities and how engagement was considered. Findings showed that the most frequent purposes of technology use were compensation and monitoring, supporting orientation, sequencing complex actions and memory impairments in a wide range of activities. The few studies that addressed the issue of engagement with technology considered how the ease of use, social appropriateness, level of personalization, dynamic adaptation and carers' mediation allowed technology to adapt to PWD's and carers' preferences and performance. Conceptual and methodological tools emerged as outcomes of the analytical process, representing an important contribution to understanding the role of technologies to increase PwD's wellbeing and orient future research.University of Huddersfield, under grants URF301-01 and URF506-01

KR3^3: An Architecture for Knowledge Representation and Reasoning in Robotics

This paper describes an architecture that combines the complementary strengths of declarative programming and probabilistic graphical models to enable robots to represent, reason with, and learn from, qualitative and quantitative descriptions of uncertainty and knowledge. An action language is used for the low-level (LL) and high-level (HL) system descriptions in the architecture, and the definition of recorded histories in the HL is expanded to allow prioritized defaults. For any given goal, tentative plans created in the HL using default knowledge and commonsense reasoning are implemented in the LL using probabilistic algorithms, with the corresponding observations used to update the HL history. Tight coupling between the two levels enables automatic selection of relevant variables and generation of suitable action policies in the LL for each HL action, and supports reasoning with violation of defaults, noisy observations and unreliable actions in large and complex domains. The architecture is evaluated in simulation and on physical robots transporting objects in indoor domains; the benefit on robots is a reduction in task execution time of 39% compared with a purely probabilistic, but still hierarchical, approach.Comment: The paper appears in the Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014