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

A MEG study of the neural substrates of semantic processing in semantic variant primary progressive aphasia

Despite a well-documented pattern of semantic memory (SM) impairment, the patterns of brain activation during semantic processing in svPPA still remain poorly understood. The current study aimed to investigate the neural substrates of residual semantic processing in the context of this significant but selective SM impairment, through the case study of one svPPA patient. One svPPA patient (EC) and six elderly controls carried out a general-level semantic categorization task (biological and manufactured objects) while their brain activity was recorded using magnetoencephalography (MEG). Despite similar behavioral performance, EC showed hyperactivation of the left inferior temporal gyrus (ITG) and right anterior temporal lobe (ATL) relative to controls. This suggests that periatrophic regions within the ATL region may support preserved semantic abilities in svPPA. These results thus contribute to our understanding of the brain regions which are recruited to compensate for bilateral atrophy of the ATL and ensure residual semantic processing in svPPA

Hierarchical Hidden Markov Model in Detecting Activities of Daily Living in Wearable Videos for Studies of Dementia

International audienceThis paper presents a method for indexing activities of daily living in videos obtained from wearable cameras. In the context of dementia diagnosis by doctors, the videos are recorded at patients' houses and later visualized by the medical practitioners. The videos may last up to two hours, therefore a tool for an efficient navigation in terms of activities of interest is crucial for the doctors. The specific recording mode provides video data which are really difficult, being a single sequence shot where strong motion and sharp lighting changes often appear. Our work introduces an automatic motion based segmentation of the video and a video structuring approach in terms of activities by a hierarchical two-level Hidden Markov Model. We define our description space over motion and visual characteristics of video and audio channels. Experiments on real data obtained from the recording at home of several patients show the difficulty of the task and the promising results of our approach

IMPACT OF ULTRAFINE AIR POLLUTANTS ON AMYLOID PEPTIDE STRUCTURE AND OLIGOMERIZATION

Amyloid beta (Aβ) peptide monomers aggregate into toxic oligomers in the human brain, leading to the progression of Alzheimer's Disease (AD), one of the common types of neurodegenerative diseases. Lifelong exposure to ambient air pollution and, particularly, ultrafine particles (UFPs) is associated with an elevated risk of the progression of AD. While the experimental studies revealed the negative impact of air pollutants on AD, the molecular interactions remain unknown. The objective of this research was to investigate the impact of ambient air pollutants on the structure and oligomerization of Aβ peptide monomers via atomistic molecular dynamics (MD) simulations, which were not demonstrated earlier. Considering the complex composition of the ambient UFPs, which usually include water-soluble ions, organic carbon (OC), elemental carbon (EC), and trace elements, this work elucidated the effect of the various compositions and concentrations of the ambient air pollutants on Aβ peptides. The systems under the study were divided as follows: i) the effect of concentration of hydrophobic UFP, modeled by C60 (EC), ii) the effect of the water-soluble ions (NO3−, NH4+,SO42−), iii) the effect of the cigarette smoke components, represented by nicotine and polycyclic aromatic hydrocarbons (PAHs), such as benzo[a]pyrene (B[a]P) and phenanthrene, iv) effect of the carbonaceous UFPs. Overall, the results of this study revealed that both the composition and concentration of air pollutants affect the structure of Aβ peptide monomers and consequent oligomerization. In particular, while the EC accelerated the oligomerization in the presence of SO42− and NO3− ions, the oligomerization was inhibited in the presence of C60 and NH4+ ions, showing the synergistic effect of EC and ambient water-soluble ions. Considering the molecular mechanisms, it should be noted that oligomerization and the growth of peptide oligomers on the surface of carbonaceous UFP models were driven by strong hydrophobic interactions. Moreover, the experimental validations demonstrated alterations in the secondary structure of Aβ peptides and enhanced growth of the β-sheets in the presence of NH4+, as well as a suppressed growth of the β-sheets in the NO3− environment due to the enhanced interactions between the peptides and nitrates. Furthermore, according to the results of the MD study, PAHs and nicotine altered the secondary structure of the Aβ monomer. Moreover, although nicotine made H-bonds with the Aβ42 monomer, resulting in the formation of a stable intermolecular cluster, phenanthrene, due to its small size, had a most significant interference with the Aβ42 monomer. In addition, B[a]P with 5 mM concentration accelerated the oligomerization of four Aβ42 peptide monomers, while the presence of B[a]P with higher concentrations 5 suppressed the oligomerization kinetics. Lastly, the carbonaceous UFPs accelerated the early aggregation of the peptide monomers to dimers, suggesting their contribution to the progression of AD. The insights revealed from this study would be helpful for the improvement of the existing policies on the reduction of air pollution, as well as for the development of new therapeutics aimed to mitigate the effects of air pollution on the progression of AD

Human Action Recognition with RGB-D Sensors

none3noHuman action recognition, also known as HAR, is at the foundation of many different applications related to behavioral analysis, surveillance, and safety, thus it has been a very active research area in the last years. The release of inexpensive RGB-D sensors fostered researchers working in this field because depth data simplify the processing of visual data that could be otherwise difficult using classic RGB devices. Furthermore, the availability of depth data allows to implement solutions that are unobtrusive and privacy preserving with respect to classic video-based analysis. In this scenario, the aim of this chapter is to review the most salient techniques for HAR based on depth signal processing, providing some details on a specific method based on temporal pyramid of key poses, evaluated on the well-known MSR Action3D dataset.Cippitelli, Enea; Gambi, Ennio; Spinsante, SusannaCippitelli, Enea; Gambi, Ennio; Spinsante, Susann

Human Action Recognition with RGB-D Sensors

Human action recognition, also known as HAR, is at the foundation of many different applications related to behavioral analysis, surveillance, and safety, thus it has been a very active research area in the last years. The release of inexpensive RGB-D sensors fostered researchers working in this field because depth data simplify the processing of visual data that could be otherwise difficult using classic RGB devices. Furthermore, the availability of depth data allows to implement solutions that are unobtrusive and privacy preserving with respect to classic video-based analysis. In this scenario, the aim of this chapter is to review the most salient techniques for HAR based on depth signal processing, providing some details on a specific method based on temporal pyramid of key poses, evaluated on the well-known MSR Action3D dataset

Implantation d'un modèle d'attention en COGENT

L’attention est une habilité cognitive qui joue un rôle primordial dans le contrôle des actions. L’attention réfère à l’allocation des ressources pour réaliser une action. L’interférence survient quand plusieurs événements réclament de l’attention. L’objet de ce mémoire est de modéliser l’attention, ce qui permettra de modéliser comment l’attention contrôle les actions humaines. En psychologie, Norman et Shallice ont construit un modèle d’organisation et de contrôle de l’attention. Ce modèle est basé sur deux composants responsables du contrôle de l’action, le “Contention Scheduling” et le “Supervisory Attentional System” . Nous présentons dans ce mémoire le modèle au complet mais l’emphase est portée sur le lien entre les deux composants. Des activités de la vie quotidienne sont simulées pour démontrer comment le modèle interagit en cas d’interruption d’une tâche routinière par une nouvelle tâche. Le temps où l’interruption survient est choisi aléatoirement. Le modèle d’attention est alors capable d’ajuster son comportement n’importe quand pendant l’action de la tâche routinière

Characterisation of metal-amyloid β peptide interactions and the effect of metals on the gene expression of amyloid precursor protein

AD is a devastating neurodegenerative condition that poses major challenges to human health, with a prevalence of around 35 million patients worldwide. One of the neuropathological hallmarks in AD patients is extracellular amyloid plaques which are composed of amyloid β peptide (Aβ) aggregates. The amyloid cascade hypothesis suggests that aggregation of the Aβ peptide into soluble oligomers and senile plaques is the main driver of AD. Metal ions are found to be present in amyloid plaques, including Cu2+, Fe2+/3+, Zn2+ and Al3+. The experimental evidence from the literatures thus far points to a role of metal ions in Aβ aggregation and pathogenesis of AD. To this end, the metal ion hypothesis for AD is proposed, which suggests that disruption of metal ion homeostasis promotes Aβ aggregation and onset of AD. However, such a link is still premature, clinical, epidemiological and molecular studies are needed. Therefore, this thesis takes a molecular approach by NMR (nuclear magnetic resonance) spectroscopy to investigate the interaction of metal ions with Aβ peptide, Aβ1-28, and to analyse potential metal chelators for future therapeutic application, and to unravel the effect of metal ions on the expression of APP gene (the gene encoding amyloid precursor protein) as well as the antagonising effect of metal chelators against metal ions in APP gene expression. The main discoveries presented in this PhD analysis are: 1. the determination of the solution structure of synthetic Aβ1-28 complexed with Al3+ by NMR spectroscopy, 2. the characterisation of the metal binding sites on Aβ1-28, 3. the upregulation of the expression of APP gene by Al3+, and 4. the presence of metal chelating ligands can lower the metal-induced APP gene expression, which should subsequently reduce the accumulation of Aβ