Flexible context aware interface for ambient assisted living

A Multi Agent System that provides a (cared for) person, the subject, with assistance and support through an Ambient Assisted Living Flexible Interface (AALFI) during the day while complementing the night time assistance offered by NOCTURNAL with feedback assistance, is presented. It has been tailored to the subject’s requirements profile and takes into account factors associated with the time of day; hence it attempts to overcome shortcomings of current Ambient Assisted Living Systems. The subject is provided with feedback that highlights important criteria such as quality of sleep during the night and possible breeches of safety during the day. This may help the subject carry out corrective measures and/or seek further assistance. AALFI provides tailored interaction that is either visual or auditory so that the subject is able to understand the interactions and this process is driven by a Multi-Agent System. User feedback gathered from a relevant user group through a workshop validated the ideas underpinning the research, the Multi-agent system and the adaptable interface

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Night optimised care technology for users needing assisted lifestyles

There is growing interest in the development of ambient assisted living services to increase the quality of life of the increasing proportion of the older population. We report on the Night Optimised Care Technology for UseRs Needing Assisted Lifestyles project, which provides specialised night time support to people at early stages of dementia. This article explains the technical infrastructure, the intelligent software behind the decision-making driving the system, the software development process followed, the interfaces used to interact with the user, and the findings and lessons of our user-centred approach

The Effect of Dosage, Gestational Age and Splenectomy on Anti-IgM Interception of Prenatal B-cell Development in Sheep

The administration of a single bolus of anti-IgM antibody to foetal lambs early in pregnancy produces prolonged B-cell depletion. The present study investigated this depletion by examining the effect, on B-cell development in the ileal Peyer's patches, of varying the timing and dosage of antibody administration and by supplementing anti-IgM with surgical splenectomy. The capacity of a 1 mg bolus of anti-IgM to deplete Peyer's patches of B cells was lost if its administration was deferred until two thirds of the way through pregnancy, but persisted beyond this time if weight-adjusted doses were used. Splenectomy of the foetus performed at an earlier age failed to extend the age at which a 1 mg dose of antibody remained effective. As the concentration of murine immunoglobulin in foetal serum was greatly reduced after 21 days, it is inferred that ongoing suppression of B-cell development is not dependent on the continued presence of murine immunoglobulin. The enduring nature of suppression could be attributable to a limited period during which differentiation of B cells from stem cells normally occurs, although further studies will be needed to investigate this and other possible explanations for the effect of anti-IgM treatment on prenatal B-cell development in sheep

Participatory research to design a novel system to support the night-time needs of people with dementia; NOCTURNAL

Strategies to support people living with dementia are broad in scope, proposing both pharmacological and non-pharmacological interventions as part of the care pathway. Assistive technologies form part of this offering as both stand-alone devices to support particular tasks and the more complex offering of the “smart home” to underpin ambient assisted living. This paper presents a technology-based system, which expands on the smart home architecture, orientated to support people with daily living. The system, NOCTURNAL, was developed by working directly with people who had dementia, and their carers using qualitative research methods. The research focused primarily on the nighttime needs of people living with dementia in real home settings. Eight people with dementia had the final prototype system installed for a three month evaluation at home. Disturbed sleep patterns, night-time wandering were a focus of this research not only in terms of detection by commercially available technology but also exploring if automated music, light and visual personalized photographs would be soothing to participants during the hours of darkness. The NOCTURNAL platform and associated services was informed by strong user engagement of people with dementia and the service providers who care for them. NOCTURNAL emerged as a holistic service offering a personalised therapeutic aspect with interactive capabilities

Generalized monotonic functional mixed models with application to modelling normal tissue complications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73586/1/j.1467-9876.2007.00606.x.pd