Bestial boredom: a biological perspective on animal boredom and suggestions for its scientific investigation

Boredom is likely to have adaptive value in motivating exploration and learning, and many animals may possess the basic neurological mechanisms to support it. Chronic inescapable boredom can be extremely aversive, and understimulation can harm neural, cognitive and behavioural flexibility. Wild and domesticated animals are at particular risk in captivity, which is often spatially and temporally monotonous. Yet biological research into boredom has barely begun, despite having important implications for animal welfare, the evolution of motivation and cognition, and for human dysfunction at individual and societal levels. Here I aim to facilitate hypotheses about how monotony affects behaviour and physiology, so that boredom can be objectively studied by ethologists and other scientists. I cover valence (pleasantness) and arousal (wakefulness) qualities of boredom, because both can be measured, and I suggest boredom includes suboptimal arousal and aversion to monotony. Because the suboptimal arousal during boredom is aversive, individuals will resist low arousal. Thus, behavioural indicators of boredom will, seemingly paradoxically, include signs of increasing drowsiness, alongside bouts of restlessness, avoidance and sensation-seeking behaviour. Valence and arousal are not, however, sufficient to fully describe boredom. For example, human boredom is further characterized by a perception that time ‘drags’, and this effect of monotony on time perception can too be behaviourally assayed in animals. Sleep disruption and some abnormal behaviour may also be caused by boredom. Ethological research into this emotional phenomenon will deepen understanding of its causes, development, function and evolution, and will enable evidence-based interventions to mitigate human and animal boredom

Distributed Computing and Monitoring Technologies for Older Patients

This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions

Assistive Technology for Independent Living with Dementia: Stylized Facts and Research Gaps

Background: Demographic change and continuously increasing spending on public health have intensified the public debate as well as deliberations on the development and deployment of new assistive technologies; particularly for dementia patients as it affects a large and increasing number of people, not only causing massive social distress, but also great economic losses. Recent advancement in assistive technologies (AT) have therefore fueled the debate on new, IT-reliant ways of providing cure and care of dementia. Still the impact on practice has been little. With this paper, we want to find out to which extent current studies have discussed the impacts of AT for dementia. Methods: We conduct a scoping review of the literature. We identified n=539 unique articles, out of which n=36 reported on impacts of AT use in the context of dementia. Based on this subset, we extracted a list of original statements, which was then further aggregated to 6 stylized facts. Results: The identified stylized facts describe common findings that can be observed in most studies reporting on IT-reliant assistive tools for dementia patients although applying different methods, focusing on different technologies, or working in different contexts. Conclusions: While the identified stylized facts indicate how much evidence behind certain common assumptions is, we additionally found that studies in the area of AT for dementia often neglect the socio-economic and ethical dimension. These are important research gaps for future work

Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Report on Typology/Segmentation of the PHS Market

This market segmentation reports for Personal Health Systems (PHS) describes the methodological background and illustrates the principles of classification and typology regarding different fragments forming this market. It discusses different aspects of the market for PHS and highlights challenges towards a stringent and clear-cut typology or defining market segmentation. Based on these findings a preliminary hybrid typology and indications and insights are created in order to be used in the continuation of the SIMPHS project. It concludes with an annex containing examples and cases studies.JRC.DDG.J.4-Information Societ

Design of a Predictive Scheduling System to Improve Assisted Living Services for Elders

International audienceAs the number of older adults increases, and with it the demand for dedicated care, geriatric residences face a shortage of caregivers, who themselves experience work overload, stress and burden. We conducted a long-term field study in three geriatric residences to understand the work conditions of caregivers with the aim of developing technologies to assist them in their work and help them deal with their burden. From this study we obtained relevant requirements and insights of design that were used to design, implement and evaluate two prototypes for supporting caregivers' tasks (e.g. electronic recording and automatic notifications), in order to validate the feasibility of their implementation in-situ and the technical requirements. The evaluation in-situ of the prototypes was conducted for a period of four weeks. The results of the evaluation, together with the data collected from six months of use, motivated the design of a predictive schedule. Such design was iteratively improved and evaluated in participative sessions with caregivers. PRESENCE, the predictive schedule we propose, triggers real-time alerts of risky situations (e.g. falls, entering off-limits areas such as the infirmary or the kitchen) and, informs caregivers of routine tasks that need to be performed (e.g. medication administration, diaper change, etc.). Moreover, PRESENCE helps caregivers to record caring tasks (such as diaper changes or medication) and wellbeing assessments (such as the mood), which are difficult to automatize. This facilitates caregiver's shift handover, and can help to train new caregivers by suggesting routine tasks and by sending reminders and timely information about the residents. It can be seen as a tool to reduce the workload of caregivers and medical staff. Instead of trying to substitute the caregiver with an automatic caring system, as proposed by others, we propose the design of our predictive schedule system that blends caregiver's assessments and measurements from sensors. We show the feasibility of predicting caregiver's tasks and a formative evaluation with caregivers that provides preliminary evidence of its utility

SMACovid-19 — autonomous monitoring system for Covid-19

Mestrado em Engenharia Industrial ESTG-IPBAtualmente, existe uma pandemia global, COVID-19, que pode provocar consequências devastadoras para a saúde humana. Além disso, pessoas idosas têm uma probabilidade maior de sofrerem os efeitos mais severos da doença. wearable devices podem monitorizar parâmetros biológicos/físicos, e uma análise de previsão aos dados resultantes deve permitir a identificação mais rápida possível de pessoas que possam estar infetadas com o vírus. Para criar um sistema com estas capacidades, desenvolveram-se os módulos health data provider e data analysis para recolher os dados e fazer as previsões, com base nesses dados, respetivamente. A plataforma FIWARE foi usada para implementar o backend do sistema, através de módulos open source ready-to-use para gerir os dados no sistema. Os médicos do Hospital da Terra Quente definiram os parâmetros biológicos/físicos de interesse e, considerando os diferentes tipos de variáveis, implementaram-se três tipos distintos de previsões: última observação, estimador linear de tendência e método aditivo Holt-Winters. As previsões obtidas são usadas para classificar o estado de uma pessoa, para um cenário de pior caso possível: provável que esteja infetado com o vírus ou provável que não esteja infetado com o vírus. As regras de classificação foram definidas pelos médicos do Hospital da Terra Quente. Os resultados obtidos são promissores e trabalho futuro pode ser feito para melhorar o sistema na inclusão de mais fontes de dados, ajuste dos métodos de previsão e na introdução de novas metodologias de classificação final.Nowadays, there exists a global pandemic, COVID-19, that may provoke devastating consequences to human health. Moreover, elder people have a higher probability to suffer the most harsh effects of the disease. By monitoring biological/physical parameters with the aid of wearable devices and applying forecast methods to the collected data, it should be feasible to identify, as soon as possible, people that may be infected with the virus. To create a system with such capabilities, a health data provider and a data analysis modules were implemented, to fetch the biological/physical data and to generate forecasts based on that data, respectively. The backend of the system was implemented through the FIWARE platform, using open source ready-to-use modules of this platform to manage the data in the system. The biological/physical parameters of interest were defined by the medical personnel of Hospital da Terra Quente and, considering the different type of variables in analysis, three types of forecasts were implemented: last observation, linear trend estimator and additive Holt-Winters method. The obtained forecasts are used, combined with a worst case scenario approach to classify the state of a person: likely to have been infected by the virus or not likely to have been infected by the virus. The classification rules were devised by the Hospital da Terra Quente medical staff. The obtained results are promising and future work can be done to improve the system in terms of providing extra data sources, fine tuning of the forecast methods and by introducing new final classification methodologies

A Mobile Healthcare Solution for Ambient Assisted Living Environments

Elderly people need regular healthcare services and, several times, are dependent of physicians’ personal attendance. This dependence raises several issues to elders, such as, the need to travel and mobility support. Ambient Assisted Living (AAL) and Mobile Health (m-Health) services and applications offer good healthcare solutions that can be used both on indoor and in mobility environments. This dissertation presents an ambient assisted living (AAL) solution for mobile environments. It includes elderly biofeedback monitoring using body sensors for data collection offering support for remote monitoring. The used sensors are attached to the human body (such as the electrocardiogram, blood pressure, and temperature). They collect data providing comfort, mobility, and guaranteeing efficiency and data confidentiality. Periodic collection of patients’ data is important to gather more accurate measurements and to avoid common risky situations, like a physical fall may be considered something natural in life span and it is more dangerous for senior people. One fall can out a life in extreme cases or cause fractures, injuries, but when it is early detected through an accelerometer, for example, it can avoid a tragic outcome. The presented proposal monitors elderly people, storing collected data in a personal computer, tablet, or smartphone through Bluetooth. This application allows an analysis of possible health condition warnings based on the input of supporting charts, and real-time bio-signals monitoring and is able to warn users and the caretakers. These mobile devices are also used to collect data, which allow data storage and its possible consultation in the future. The proposed system is evaluated, demonstrated and validated through a prototype and it is ready for use. The watch Texas ez430-Chronos, which is capable to store information for later analysis and the sensors Shimmer who allow the creation of a personalized application that it is capable of measuring biosignals of the patient in real time is described throughout this dissertation