Pervasive assistive technology for people with dementia : a UCD case

Smart mobile and wearable technology offers exciting opportunities to support people with dementia (PwD). Its ubiquity and popularity could even benefit user adoption – a great challenge for assistive technology (AT) for PwD that calls for user-centred design (UCD) methods. This study describes a user-centred approach to developing and testing AT based on off-the-shelf pervasive technologies. A prototype is created by combining a smartphone, smartwatch and various applications to offer six support features. This is tested among five end-users (PwD) and their caregivers. Controlled usability testing was followed by field testing in a real-world context. Data is gathered from video recordings, interaction logs, system usability scale questionnaires, logbooks, application usage logs and interviews structured on the unified theory of acceptance and use of technology model. The data is analysed to evaluate usability, usefulness and user acceptance. Results show some promise for user adoption, but highlight challenges to be overcome, emphasising personalisation and familiarity as key considerations. The complete findings regarding usability issues, usefulness of support features and four identified adoption profiles are used to provide a set of recommendations for practitioners and further research. These contribute toward UCD practices for improved smart, pervasive AT for dementia

Analyses of Functional Data

motivated the present work. Paper 1 contains the statistical analysis made to find the calibration function between sensory assessments and rheological measurements of low-fat spreads. The aim of the study was to describe the relationship between rheological properties and sensory assessments of texture properties for ten commercial low-fat spreads. The rheological measurements in focus are processes in temperature and to extract the information on the product contained in the process smooth principal component analysis was carried out. Paper 2 introduces a non-parametric maximum likelihood estimator within the self modelling regression framework. The data analysed consists of nine protein profiles obtained by capillary electrophoresis on feta cheese. Due to varying experimental conditions the nine curves are shifted on the time axis. To account for this variation in timing between the curves, the data is modelled as the same shape function shifted by individual un-observed random sh

High CD34 surface expression in BCP-ALL predicts poor induction therapy response and is associated with altered expression of genes related to cell migration and adhesion

Minimal residual disease (MRD) constitutes the most important prognostic factor in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Flow cytometry is widely used in MRD assessment, yet little is known regarding the effect of different immunophenotypic subsets on outcome. In this study of 200 BCP-ALL patients, we found that a CD34-positive, CD38 dim-positive, nTdT dim-positive immunophenotype on the leukemic blasts was associated with poor induction therapy response and predicted an MRD level at the end of induction therapy (EOI) of ≥ 0.001. CD34 expression was strongly and positively associated with EOI MRD, whereas CD34-negative patients had a low relapse risk. Further, CD34 expression increased from diagnosis to relapse. CD34 is a stemness-associated cell-surface molecule, possibly involved in cell adhesion/migration or survival. Accordingly, genes associated with stemness were overrepresented among the most upregulated genes in CD34-positive leukemias, and protein–protein interaction networks showed an overrepresentation of genes associated with cell migration, cell adhesion, and negative regulation of apoptosis. The present work is the first to demonstrate a CD34-negative immunophenotype as a good prognostic factor in ALL, whereas high CD34 expression is associated with poor therapy response and an altered gene expression profile reminiscent of migrating cancer stem-like cells