No description available.

The overall purpose of the study was the identification of factors which influence the freedom of physically disabled people, within South African society, to make choices that will enable them to conduct their daily lives independently. Qualitative research methods (observation and semi-structured interviews) were utilised to explore the problem from the disabled person's perspective. In total there were ten participants, sampling being purposive and opportunistic. The study was essentially narrative, with the results analysed and grouped thematically. Factors influencing independence related to the individual's functioning, as well as the social environment and the study's setting in Mitchells Plain, Cape Town. The relative strength of each factor varied at any one time for a given subject, and between the respondents. Overall there was strong agreement amongst participants and with the literature. Recommendations made related to future research, student training and occupational therapy practise.

La plupart des travaux réalisés dans le domaine de l'assistance à l'autonomie à domicile (AAL) reposent sur l'utilisation de capteurs visuels et audio tels que des caméras. Or, ces capteurs sont souvent rejetés par le patient à cause de leur caractère invasif. Des approches alternatives requièrent l'utilisation de capteurs embarqués sur la personne (GPS, bracelets électroniques ou puces RFID dans les vêtements...), et leur pertinence est donc ramenée à l'hypothèse que les personnes les portent effectivement, sans jamais les rejeter ni les oublier. Pour ces raisons, dans cette thèse, nous trouvons plus pertinentes les approches uniquement basées sur l'utilisation de capteurs binaires intégrés dans l'habitat, tels que les détecteurs de mouvements, les tapis sensitifs ou les barrières optiques. Dans un tel contexte technologique, il devient intéressant d'utiliser les paradigmes, les modèles et les outils des systèmes à événement Discrets (SED), initialement plutôt développés pour la modélisation, l'analyse et la commande des systèmes industriels complexes. Dans ces travaux de thèse, l'objectif est de construire une approche pour la modélisation et le suivi des habitudes de vie, basée sur les modèles et les paradigmes des SED et répondant à une problématique qui s'énonce de la manière suivante : L'objectif est de développer un cadre global pour découvrir et reconnaître les activités de la vie quotidienne d'un habitant vivant seul dans une maison intelligente. Cette maison intelligente doit être équipée uniquement de capteurs binaires, l'étiquetage par des experts des activités observées ne doit pas être nécessaire et les activités peuvent être représentées par des modèles probabilistes. La première méthode présentée dans cette thèse permet, à partir d'une base de données d'apprentissage et d'une description experte des activités à modéliser listées par des médecins, de construire pour chaque activité un modèle sous la forme d'un automate à état-fini probabiliste (PFA). La seconde méthode développée lors de cette thèse permet d'estimer en temps réel, à partir des seules données observées par les capteurs ambiants, quelle activité la personne observée réalise effectivement. Les méthodes décrites dans cette thèse sont illustrées en utilisant les données générées localement via l'utilisation d'un appartement prêté par ENS Paris-Saclay équipé pour répondre aux besoins expérimentaux de cette thèse. / Most of the work done in the field of ambient assisted living (AAL) is based on the use of visual and audio sensors such as cameras. However, these sensors are often rejected by the patient because of their invasiveness. Alternative approaches require the use of sensors embedded on the person (GPS, electronic wristbands or RFID chips in clothing ...), and their relevance is therefore reduced to the assumption that people actually wear them, without rejecting nor forgetting them. For these reasons, in this thesis, we find more relevant the approaches based on the use of binary sensors integrated into the habitat only, such as motion detectors, sensory mats or optical barriers. In such a technological context, it becomes interesting to use paradigms, models and tools of Discrete Event Systems (DES), initially developed for modeling, analysis and control of complex industrial systems. In this thesis work, the goal is to build an activity of daily living modeling and monitoring approach, based on the models and the paradigm of the DES and answering a problem that is expressed as follows:The objective is to develop a global framework to discover and recognise activities of daily living of an inhabitant living alone in a smart home. This smart home have to be equipped with binary sensors only, expert labeling of activities should not be needed and activities can be represented by probabilistic models. The first method presented in this thesis allows to build a probabilistic finite-state automata (PFA) from a learning database and an expert description of the activities to be modeled given by the medical staff. The second method developed during this thesis estimates, according to the observations, the activity performed by the monitored inhabitant. The methods described in this thesis are applied on data generated using an apartment lent by ENS Paris-Saclay and equipped according the experimental needs of this thesis. / La maggior parte dei lavori nel settore dell’Ambient Assisted Living (AAL) si basasull’uso di sensori visivi e audio come le telecamere. Tuttavia, questi sensori sonospesso rifiutati dal paziente a causa della loro natura invasiva. Gli approcci alternativi richiedono l’uso di sensori integrati nella persona (GPS, bracciali elettronici o chipRFID...), e la loro rilevanza è quindi ridotta all’ipotesi che le persone li indossino effettivamente, senza mai rifiutarli o dimenticarli.Per questi motivi, in questa tesi, troviamo approcci più rilevanti basati esclusivamente sull’uso di sensori binari integrati nell’habitat, come rilevatori di movimento,tappeti sensoriali o barriere fotoelettriche.In tale contesto tecnologico, diventa interessante utilizzare i paradigmi, i modelli egli strumenti dei sistemi ad eventi discreti (SED), inizialmente sviluppati per la modellazione, l’analisi e il controllo di sistemi industriali complessi.In questo lavoro di tesi, l’obiettivo è quello di presentare un metodo per la modellazione e il monitoraggio delle abitudini di vita, basato sui modelli e paradigmi di SEDe rispondendo ad un problema che si esprime come segue : L’obiettivo è quello di sviluppare un quadro globale per rivelare e riconoscere le attività della vita quotidiana di una persona che abita da sola in una smart home chedovrebbe essere dotata solo di sensori binari. Inoltre si suppone che non sia necessarial’etichettatura delle attività osservate da parte di un esperto e tali attività sono rappresentate da modelli probabilistici.Il primo metodo presentato in questa tesi permette di costruire un modello probabilistico di automa a stati finiti (PFA) ottenuto da un database di apprendimento e unadescrizione delle attività da parte di medici. Il secondo metodo sviluppato in questa tesi stima, alla luce delle osservazioni, qualeattività svolge la persona osservata. I metodi descritti sono illustrati utilizzando dati generati localmente attraverso l’usodi un appartamento messo a disposizione da ENS Paris-Saclay e attrezzato per soddisfarele esigenze sperimentali di questa tesi.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18858号 / 医博第3969号 / 新制||医||1008(附属図書館) / 31809 / 京都大学大学院医学研究科医学専攻 / (主査)教授 福原 俊一, 教授 古川 壽亮, 教授 村井 俊哉 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

No description available.

The purpose of this study was to summarize the effects of physical activity (PA) as a nonpharmacological preventative measure in people at risk of Alzheimer's disease (AD) or all-cause dementia. It was hypothesized that persons at risk of AD or all-cause dementia who engage in sustained and continuous PA would fare better in terms of physical health, cognition, and activities of daily living (ADLs). A systematic literature review was conducted in the Cumulative Index to Nursing and Allied Health Literature (CINAHL) using 12 keywords. Studies were included if they were randomized controlled trials with people at risk of AD or all-cause dementia reporting outcomes of PA on three domains, namely: physical health, cognition, or ADLs. Data was extracted using the Matrix Method and results were summarized using applied thematic analyses. Out of 55 records screened, eight met the inclusion criteria for data extraction. Findings indicate statistically significant improvement in four [HLC1] metrics of physical health such as balance, strength, stamina, and oxygenation. Findings also showed statistically significant improvement in four measures of cognition (short-term memory, lucidity, executive function, and language ability). Two studies reported statistically significant improvement in two measures of ADLs (less assistance to complete daily tasks and execution of instrumental activities). Overall, studies showed that physical health, cognition, and two measures of ADLs of people at risk of AD and all-cause dementia improve with sustained and continuous PA, although the interventions and measures were extremely heterogeneous. Future research and intervention efforts should align PA efforts with current universal recommendations to improve outcomes in the general population and in those at risk of AD and all-cause dementia.

No description available.

No description available.

Trough previous research we have knowledge about the connection between balance in daily life and the experience of health. The psychological or stressrelated ill health increases despite more people receiving care and treatment. It is therefore a central issue to shed further light on whether we provide the right care based on the perspective of the individuals. The purpose of the study was to describe experiences from adult individuals on sick leave due to psychological or stress related ill health regarding maintaining balance in everyday activities. Data were generated through individual narrative interviews with individuals with psychological or stress related illness, from primary care and analysed using a narrative analysis. The analysis of the data resulted in four themes called strategies for maintaining balance, barriers to balancing strategies to maintaining balance, roles and habits that affects the ability to maintain balance, new experiences that affects the ability to maintain balance. Results show that there is a complexity to maintain balance in daily living and there are many components that effects the ability and conditions to maintain a balance in daily life that promotes health. The results could give a deeper understanding about the need for care through the individuals experience and highlight occupational therapy and the occupational therapist role. This regarding working with the ability to delimit in activity as a step towards developing care and treatment for individuals with psychological or stress related illness. And raise the perspective on the importance of creating sustainability perspective and from socioeconomic gain

This work presents comprehensive analytics of trajectories of functional loss and recovery using sequence analysis and clustering techniques. The study focuses on a large dataset consisting of assessments of activities of daily living conducted among nursing home residents. The first main part of this research involves converting the assessments into sequences of disability combinations and utilizing graphical tools and various indicators to gain valuable insights into the trajectories of functional disabilities over time. In the second part of the research, a novel clustering approach is introduced that combines Markov models with distance-based techniques. This hybrid methodology results in 13 distinct clusters of trajectories. The clusters are thoroughly examined, and representative sets are carefully selected based on various criteria. This selection process ensures that the chosen sets accurately represent the characteristics of each cluster. The findings of this study have significant implications for healthcare systems, including developing predictive models which can be utilized to forecast the trajectory of individual patients based on their cluster membership. This enables healthcare providers to anticipate disease progression, tailor treatments, and dynamically adjust care plans, resulting in improved patient outcomes and the overall quality of care. Moreover, the information derived from the analytics can aid in optimizing healthcare systems by facilitating resource allocation and cost optimization. The insights gained can also guide policymakers and families in planning appropriate care for patients. This research advances healthcare decision-making and ensures appropriate support. / Thesis / Master of Science (MSc) / The ability to independently perform activities of daily living (ADLs) is a crucial indicator of an individual's health status, and the loss of this ability can have a profound impact on their overall quality of life. Our research focuses on analyzing the trajectories of patients as they experience functional decline and recovery. While various techniques have been utilized to explore ADL trajectories, this study stands out by employing clustering and sequence analysis approaches to examine different groups of trajectories. To overcome the computational challenges involved, we propose a combined clustering approach. This hybrid approach consists of two phases: applying a Markov model prior to distance-based algorithms. The findings derived from our research hold significant applications in optimizing healthcare systems, improving health outcomes, facilitating the development of targeted and effective interventions that support patients in preserving their independence, and enhancing the quality of care.