2,285 research outputs found

    Ubiquitous Health Management System with Watch-Type Monitoring Device for Dementia Patients

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    For patients who have a senile mental disorder such as dementia, the quantity of exercise and amount of sunlight are an important clue for doses and treatment. Therefore, monitoring daily health information is necessary for patients’ safety and health. A portable and wearable sensor device and server configuration for monitoring data are needed to provide these services for patients. A watch-type device (smart watch) that patients wear and a server system are developed in this paper. The smart watch developed includes a GPS, accelerometer, and illumination sensor, and can obtain real time health information by measuring the position of patients, quantity of exercise, and amount of sunlight. The server system includes the sensor data analysis algorithm and web server used by the doctor and protector to monitor the sensor data acquired from the smart watch. The proposed data analysis algorithm acquires the exercise information and detects the step count in patients’ motion acquired from the acceleration sensor and verifies the three cases of fast pace, slow pace, and walking pace, showing 96% of the experimental results. If developed and the u-Healthcare System for dementia patients is applied, higher quality medical services can be provided to patients

    Medical data processing and analysis for remote health and activities monitoring

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    Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

    The Ethical Implications of Personal Health Monitoring

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    Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes include privacy, autonomy, obtrusiveness and visibility, stigma and identity, medicalisation, social isolation, delivery of care, and safety and technological need. The issues around each of these are discussed. The system / lifeworld perspective of Habermas is applied to develop an understanding of the role of PHMs as mediators of communication between the institutional and the domestic environment. Furthermore, links are established between the ethical issues to demonstrate that the ethics of PHM involves a complex network of ethical interactions. The paper extends the discussion of the critical effect PHMs have on the patient’s identity and concludes that a holistic understanding of the ethical issues surrounding PHMs will help both researchers and practitioners in developing effective PHM implementations

    Remember to remember: A feasibility study adapting wearable technology to the needs of people aged 65 and older with Mild Cognitive Impairment (MCI) and Alzheimer's Dementia

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    Designing for a healthy life includes addressing the needs of an ageing population. The number of people aged 65 and older with mild cognitive impairment and dementia is rising. Whilst there is todate no pharmacological cure, treatments for symptoms and studies into the effect of nonpharmacological interventions have increasingly become available, with the goals of maintaining and supporting cognitive function, helping the person compensate for impairments, and improving the quality of life. Promising yet nascent is the use of wearable technology for cognitive rehabilitation. We conducted an exploratory feasibility study adapting wearable technologies to support the abovementioned elderly user group remember to remember their daily activities such as non-routine appointments. Six design concepts with smartwatches, smart bands, smartphones, smart calendar boards, NFC tags, and augmented reality glasses were sketched and two low-fidelity prototypes, Memofy and Komihu, were developed and tested with three patients and their caregivers. Technology acceptance was high both amongst patients and health personnel, encouraging further in-depth and longitudinal tests for health outcomes

    ANGELAH: A Framework for Assisting Elders At Home

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    The ever growing percentage of elderly people within modern societies poses welfare systems under relevant stress. In fact, partial and progressive loss of motor, sensorial, and/or cognitive skills renders elders unable to live autonomously, eventually leading to their hospitalization. This results in both relevant emotional and economic costs. Ubiquitous computing technologies can offer interesting opportunities for in-house safety and autonomy. However, existing systems partially address in-house safety requirements and typically focus on only elder monitoring and emergency detection. The paper presents ANGELAH, a middleware-level solution integrating both ”elder monitoring and emergency detection” solutions and networking solutions. ANGELAH has two main features: i) it enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and ii) provides a solid framework for creating and managing rescue teams composed of individuals willing to promptly assist elders in case of emergency situations. A prototype of ANGELAH, designed for a case study for helping elders with vision impairments, is developed and interesting results are obtained from both computer simulations and a real-network testbed

    Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management

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    The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.Consejo Nacional de Ciencia y Tecnologia (CONACyT)Sonora Institute of Technology (ITSON) via the PROFAPI program PROFAPI_2020_0055Spanish Ministry of Science, Innovation and Universities (MICINN) project "Advanced Computing Architectures and Machine Learning-Based Solutions for Complex Problems in Bioinformatics, Biotechnology and Biomedicine" RTI2018-101674-B-I0

    Development of a Sensor-Based Behavioral Monitoring Solution to Support Dementia Care

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    Background: Mobile and wearable technology presents exciting opportunities for monitoring behavior using widely available sensor data. This could support clinical research and practice aimed at improving quality of life among the growing number of people with dementia. However, it requires suitable tools for measuring behavior in a natural real-life setting that can be easily implemented by others. Objective: The objectives of this study were to develop and test a set of algorithms for measuring mobility and activity and to describe a technical setup for collecting the sensor data that these algorithms require using off-the-shelf devices. Methods: A mobility measurement module was developed to extract travel trajectories and home location from raw GPS (global positioning system) data and to use this information to calculate a set of spatial, temporal, and count-based mobility metrics. Activity measurement comprises activity bout extraction from recognized activity data and daily step counts. Location, activity, and step count data were collected using smartwatches and mobile phones, relying on open-source resources as far as possible for accessing data from device sensors. The behavioral monitoring solution was evaluated among 5 healthy subjects who simultaneously logged their movements for 1 week. Results: The evaluation showed that the behavioral monitoring solution successfully measures travel trajectories and mobility metrics from location data and extracts multimodal activity bouts during travel between locations. While step count could be used to indicate overall daily activity level, a concern was raised regarding device validity for step count measurement, which was substantially higher from the smartwatches than the mobile phones. Conclusions: This study contributes to clinical research and practice by providing a comprehensive behavioral monitoring solution for use in a real-life setting that can be replicated for a range of applications where knowledge about individual mobility and activity is relevant

    Connectivity for Healthcare and Well-Being Management: Examples from Six European Projects

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    Technological advances and societal changes in recent years have contributed to a shift in traditional care models and in the relationship between patients and their doctors/carers, with (in general) an increase in the patient-carer physical distance and corresponding changes in the modes of access to relevant care information by all groups. The objective of this paper is to showcase the research efforts of six projects (that the authors are currently, or have recently been, involved in), CAALYX, eCAALYX, COGKNOW, EasyLine+, I2HOME, and SHARE-it, all funded by the European Commission towards a future where citizens can take an active role into managing their own healthcare. Most importantly, sensitive groups of citizens, such as the elderly, chronically ill and those suffering from various physical and cognitive disabilities, will be able to maintain vital and feature-rich connections with their families, friends and healthcare providers, who can then respond to, and prevent, the development of adverse health conditions in those they care for in a timely manner, wherever the carers and the people cared for happen to be

    When technology cares for people with dementia:A critical review using neuropsychological rehabilitation as a conceptual framework

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    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

    Technology and dementia: the future is now

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    Background: Technology has multiple potential applications to dementia from diagnosis and assessment to care delivery and supporting ageing in place. Objectives: To summarise key areas of technology development in dementia and identify future directions and implications. Method: Members of the US Alzheimer’s Association Technology Professional Interest Area involved in delivering the annual pre-conference summarised existing knowledge on current and future technology developments in dementia. Results: The main domains of technology development are as follows: (i) diagnosis, assessment and monitoring, (ii) maintenance of functioning, (iii) leisure and activity, (iv) caregiving and management. Conclusions: The pace of technology development requires urgent policy, funding and practice change, away from a narrow medical approach, to a holistic model that facilitates future risk reduction and pre- vention strategies, enables earlier detection and supports implementation at scale for a meaningful and fulfilling life with dementia
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