scispace - formally typeset
Search or ask a question
Book ChapterDOI

Activity Recognition and Dementia Care in Smart Home

TL;DR: An assistive dementia care system through smart home that offers functional assistance to the dement occupant during critical situations without the help of caretaker is proposed.
Abstract: Smart home is a ubiquitous environment that aims to offer Ambient Assisted Living (AAL) to its occupants. The activity modeling framework proposed in this research work skillfully integrates ambient intelligence into the home environment by a collective process of activity recognition, abnormality detection, and decision making. Moreover, the activity modeling strategy employed in this research work efficiently models both the data and domain knowledge for activity recognition. The primary task in designing an activity recognition system involves the construction of activity model that represents occupant’s Activities of Daily Living (ADL). To achieve activity recognition and abnormality detection competently, it is essential for the activity modeling strategy to consider the design challenges of uncertainty modeling, contextual modeling, composite modeling, activity diversity, and activity dynamics. The challenges of activity dynamics and data uncertainty are well addressed through data-driven approaches, whereas the challenges of activity granularity, contextual knowledge, and activity diversity are well addressed through knowledge-driven approaches. Therefore, activity recognition frameworks are proposed in this research work, where the first framework represents the activity model as a Markov Logic Network and the second framework represents the activity model as a probabilistic ontology. Each of these approaches offers both uncertainty and contextual modeling for activity recognition by integrating data-driven and knowledge-driven techniques. Moreover, this research proposes an assistive dementia care system through smart home that offers functional assistance to the dement occupant during critical situations without the help of caretaker.
References
More filters
Journal ArticleDOI
TL;DR: Experiments with a real-world database and knowledge base in a university domain illustrate the promise of this approach to combining first-order logic and probabilistic graphical models in a single representation.
Abstract: We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the domain, it specifies a ground Markov network containing one feature for each possible grounding of a first-order formula in the KB, with the corresponding weight. Inference in MLNs is performed by MCMC over the minimal subset of the ground network required for answering the query. Weights are efficiently learned from relational databases by iteratively optimizing a pseudo-likelihood measure. Optionally, additional clauses are learned using inductive logic programming techniques. Experiments with a real-world database and knowledge base in a university domain illustrate the promise of this approach.

2,916 citations

Journal ArticleDOI
01 Jan 1988
TL;DR: Analysis of total (summed) scores revealed a close correlation between all four methods: a difference of 4/20 points was likely to reflect a genuine difference, and in individual items, most disagreement was minor and involved the definition of middle grades.
Abstract: The Barthel Index is a valid measure of disability. In this study we investigated the reliability of four different methods of obtaining the score in 25 patients: self-report, asking a trained nurse who had worked with the patient for at least one shift, and separate testing by two skilled observers within 72 hours of admission. Analysis of total (summed) scores revealed a close correlation between all four methods: a difference of 4/20 points was likely to reflect a genuine difference. In individual items, most disagreement was minor and involved the definition of middle grades. Asking an informed nurse or relative was as reliable as testing, and is quicker.

2,319 citations

Journal ArticleDOI
01 Nov 2012
TL;DR: A comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition, making a primary distinction in this paper between data-driven and knowledge-driven approaches.
Abstract: Research on sensor-based activity recognition has, recently, made significant progress and is attracting growing attention in a number of disciplines and application domains. However, there is a lack of high-level overview on this topic that can inform related communities of the research state of the art. In this paper, we present a comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition. We first discuss the general rationale and distinctions of vision-based and sensor-based activity recognition. Then, we review the major approaches and methods associated with sensor-based activity monitoring, modeling, and recognition from which strengths and weaknesses of those approaches are highlighted. We make a primary distinction in this paper between data-driven and knowledge-driven approaches, and use this distinction to structure our survey. We also discuss some promising directions for future research.

944 citations

Journal ArticleDOI
TL;DR: This paper provides a survey of the technologies that comprise ambient intelligence and of the applications that are dramatically affected by it and specifically focuses on the research that makes AmI technologies ''intelligent''.

921 citations

Journal ArticleDOI
TL;DR: In 2010, Alzheimer's Disease International presented estimates of the global cost of illness (COI) of dementia, and new studies have been conducted, and the number of people with dementia has increased.
Abstract: Introduction In 2010, Alzheimer's Disease International presented estimates of the global cost of illness (COI) of dementia. Since then, new studies have been conducted, and the number of people with dementia has increased. Here, we present an update of the global cost estimates. Methods This is a societal, prevalence-based global COI study. Results The worldwide costs of dementia were estimated at United States (US) $818 billion in 2015, an increase of 35% since 2010; 86% of the costs occur in high-income countries. Costs of informal care and the direct costs of social care still contribute similar proportions of total costs, whereas the costs in the medical sector are much lower. The threshold of US $1 trillion will be crossed by 2018. Discussion Worldwide costs of dementia are enormous and still inequitably distributed. The increase in costs arises from increases in numbers of people with dementia and in increases in per person costs.

768 citations