A conceptual approach to enhance the well-being of elderly people

The number of elderly people living alone is increasing. Consequently, a lot of research works have been addressing this issue in order to propose solutions that can enhance the quality of life of elderly people. Most of them have been concerned in dealing with objective issues such as forgetfulness or detecting falls. In this paper, we propose a conceptual approach of a system that intends to enhance the daily sense of user’s well-being. For that, our proposal consists in a system that works as a social network and a smartwatch application that works unobtrusively and collects the user’s physiological data. In addition, we debate how important features such as to detect user’s affective states and to potentiate user’s memory could be implemented. Our study shows that there are still some important limitations which affect the success of applications built in the context of elderly care and which are mostly related with accuracy and usability of this kind of system. However, we believe that with our approach we will be able to address some of those limitations and define a system that can enhance the well-being of elderly people and improve their cognitive capabilities.The work presented in this paper has been developed under the EUREKA - ITEA3 Project PHE (PHE-16040), and by National Funds through FCT (Fundação para a Ciência e a Tecnologia) under the projects UID/EEA/00760/2019 and UID/CEC/00319/2019 and by NORTE-01-0247-FEDER-033275 (AIRDOC - “Aplicação móvel Inteligente para suporte individualizado e monitorização da função e sons Respiratórios de Doentes Obstrutivos Crónicos ”) by NORTE 2020 (Programa Operacional Regional do Norte)

Technology assisted risk assessment in homecare

The home is a key environment for geriatric care. Research has demonstrated patients discharged to their homes are at a high risk of readmission of transitioning to homecare. The ability for care providers to predict and mitigate risk is limited in this environment. Significant observational requirements hinder continued diagnosis which limits timely interventions before a readmission event. Technology is used to resolve this issue and provide enhanced risk assessments by gathering data, however these technologies present a wide variety of challenges including barriers to use and ethical considerations which hinder an effective solution. This paper seeks to examine the necessary observations homecare providers require to form effective risk assessments and interventions in the home. This is achieved by remote monitoring through Bluetooth low energy (BLE) sensors for the common causes of hospital readmissions including observed difficulties in activities of daily living (ADL), heart rate fluctuations and falls. Risk is assessed by examining these factors as events to deduce behaviour or apparent reduction in capacity to function in daily life. Results obtained when using BLE sensors, heart rate monitors and fall detectors show it is possible to observe and record events of interest to health care providers in the provision of geriatric homecare. Patterns within sensor data could be used in the home environment to form an effective patient risk analysis given remote monitoring access to a patient and prescribed care plan to evaluate outcomes and possibility of readmission. Further experiments will test and validate the risk assessment analysis formed in this paper

Deployment of a smart telecare system to carry out an intelligent health monitoring at home

Information and Communication Technologies together appropriate reasoning tools can add value to current telecare systems, including smart tele-monitoring solutions to enhance the capability for identifying risk situations at home. Cooperation between Home Area Networks (HAN) and Body Area Networks (BAN) at home can provide smart systems to support effective health solutions for ageing people living alone, improving service quality and security to the users and relatives. This paper details the development of a reasoning platform to monitor situations of the person at home, and react in risk situations that demanding care support of remote careers. The system integrates BAN and HAN with intelligent agents, whose behavior is defined by ontologies and rules. The system manages environmental and user data to proactively detect risk situations, and dynamically adjust its behavior to trigger the adequate problem solve mechanisms. A development methodology was also adapted to sustain knowledge acquisition process from experts in all stages of the development process and to create the reasoning logic adapted to the users in telecare scenario. Thus, the platform is flexible and easily customizable, according hardware conditions and user profile

Communication Needs of Elderly at Risk of Falls and their Remote Family

The aging population experiences increased health risks, both physical and emotional. Two such risks are those of isolation and falling. This papers draws from HCI literature in these two independent research areas to explore the needs of family communication with elderly parents at risk of falls. We report on a study with 7 elderly parents and 3 of adult children, as well as a group interview with 12 elderly living in a sheltered accommodation. Findings indicate important emotional needs on both parts: adult children’s anxiety for the wellbeing of their parents at risk of falls, and elderly’s need for autonomy and their appreciation for an aesthetic design. We concluded with implications of these findings for designing for family communication in this challenging context

What features and functions are desired in telemedical services targeted at polish older adults delivered by wearable medical devices? : pre-COVID-19 flashback

The emerging wearable medical devices open up new opportunities for the provision of health services and promise to accelerate the development of novel telemedical services. The main objective of this study was to investigate the desirable features and applications of telemedical services for the Polish older adults delivered by wearable medical devices. The questionnaire study was conducted among 146 adult volunteers in two cohorts (C.1: <65 years vs. C.2: ≥65 years). The analysis was based on qualitative research and descriptive statistics. Comparisons were performed by Pearson’s chi-squared test. The questionnaire, which was divided into three parts (1-socio-demographic data, needs, and behaviors; 2-health status; 3-telemedicine service awareness and device concept study), consisted of 37 open, semi-open, or closed questions. Two cohorts were analyzed (C.1: n = 77; mean age = 32 vs. C.2: n = 69; mean age = 74). The performed survey showed that the majority of respondents were unaware of the telemedical services (56.8%). A total of 62.3% of C.1 and 34.8% of C.2 declared their understanding of telemedical services. The 10.3% of correct explanations regarding telemedical service were found among all study participants. The most desirable feature was the detection of life-threatening and health-threatening situations (65.2% vs. 66.2%). The findings suggest a lack of awareness of telemedical services and the opportunities offered by wearable telemedical devices

Aging-in-place: The influence of Covid-19 on smart device acceptance

Covid-19 and the increasing population of older adults in developed countries have increased the need for alternative solutions for preventative health and long-term care. Smart homes and other assistive technology have been proposed as a solution to detect health problems early and prevent major issues later, provide better care access through telemedicine solutions, and support the autonomy of older adults with cognitive or physical issues who wish to continue to live in their homes. Rural older adults' acceptance of assistive technology is understudied compared to other groups, but the few studies available indicated that many tend to reject it. However, Covid-19 may increase interest in the technology, and the goal of this project was to determine if rural Oklahoman older adults' acceptance of the technology has increased enough for it to be implemented. This is a qualitative study that used Grounded Theory coding to determine common themes of participants to determine the level of acceptance. Interviews indicated that acceptance is still low for some devices but that rural older Oklahomans may consider other remote health instruments for specific conditions, fall detection, and home security devices if recommended by a doctor and if their issues with the technology, such as self-image, independence, and financial concerns, were resolved. If the acceptance of these devices is increased in the future, it may be possible to provide better preventative care for rural Oklahomans, detecting problems early and treating the main issues to delay major health complications. This could narrow healthcare disparities between urban and rural older adults, especially during special situations like pandemics

Devices and Data Workflow in COPD Wearable Remote Patient Monitoring: A Systematic Review

Background: With global increase in Chronic Obstructive Pulmonary Disease (COPD) prevalence and mortality rates, and socioeconomical burden continuing to rise, current disease management strategies appear inadequate, paving the way for technological solutions, namely remote patient monitoring (RPM), adoption considering its acute disease events management benefit. One RPM’s category stands out, wearable devices, due to its availability and apparent ease of use. Objectives: To assess the current market and interventional solutions regarding wearable devices in the remote monitoring of COPD patients through a systematic review design from a device composition, data workflow, and collected parameters description standpoint. Methods: A systematic review was conducted to identify wearable device trends in this population through the development of a comprehensive search strategy, searching beyond the mainstream databases, and aggregating diverse information found regarding the same device. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed, and quality appraisal of identified studies was performed using the Critical Appraisal Skills Programme (CASP) quality appraisal checklists. Results: The review resulted on the identification of 1590 references, of which a final 79 were included. 56 wearable devices were analysed, with the slight majority belonging to the wellness devices class. Substantial device heterogeneity was identified regarding device composition type and wearing location, and data workflow regarding 4 considered components. Clinical monitoring devices are starting to gain relevance in the market and slightly over a third, aim to assist COPD patients and healthcare professionals in exacerbation prediction. Compliance with validated recommendations is still lacking, with no devices assessing the totality of recommended vital signs. Conclusions: The identified heterogeneity, despite expected considering the relative novelty of wearable devices, alerts for the need to regulate the development and research of these technologies, specially from a structural and data collection and transmission standpoints.Introdução: Com o aumento global das taxas de prevalência e mortalidade da Doença Pulmonar Obstrutiva Crónica (DPOC) e o seu impacto socioeconómico, as atuais estratégias de gestão da doença parecem inadequadas, abrindo caminho para soluções tecnológicas, nomeadamente para a adoção da monitorização remota, tendo em conta o seu benefício na gestão de exacerbações de doenças crónicas. Dentro destaca-se uma categoria, os dispositivos wearable, pela sua disponibilidade e aparente facilidade de uso. Objetivos: Avaliar as soluções existentes, tanto no mercado, como na área de investigação, relativas a dispositivos wearable utilizados na monitorização remota de pacientes com DPOC através de uma revisão sistemática, do ponto de vista da composição do dispositivo, fluxo de dados e descrição dos parâmetros coletados. Métodos: Uma revisão sistemática foi realizada para identificar tendências destes dispositivos, através do desenvolvimento de uma estratégia de pesquisa abrangente, procurando pesquisar para além das databases convencionais e agregar diversas informações encontradas sobre o mesmo dispositivo. Para tal, foram seguidas as diretrizes PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), e a avaliação da qualidade dos estudos identificados foi realizada utilizando a ferramenta CASP (Critical Appraisal Skills Programme). Resultados: A revisão resultou na identificação de 1590 referências, das quais 79 foram incluídas. Foram analisados 56 dispositivos wearable, com a ligeira maioria a pertencer à classe de dispositivos de wellness. Foi identificada heterogeneidade substancial nos dispositivos em relação à sua composição, local de uso e ao fluxo de dados em relação a 4 componentes considerados. Os dispositivos de monitorização clínica já evidenciam alguma relevância no mercado e, pouco mais de um terço, visam auxiliar pacientes com DPOC e profissionais de saúde na previsão de exacerbações. Ainda assim, é notória a falta do cumprimento das recomendações validadas, não estando disponíveis dispositivos que avaliem a totalidade dos sinais vitais recomendados. Conclusão: A heterogeneidade identificada, apesar de esperada face à relativa novidade dos dispositivos wearable, alerta para a necessidade de regulamentação do desenvolvimento e investigação destas tecnologias, especialmente do ponto de vista estrutural e de recolha e transmissão de dados

EchoWear: Smartwatch Technology for Voice and Speech Treatments of Patients with Parkinson’s Disease

About 90 percent of people with Parkinson\u27s disease (PD) experience decreased functional communication due to the presence of voice and speech disorders associated with dysarthria that can be characterized by monotony of pitch (or fundamental frequency), reduced loudness, irregular rate of speech, imprecise consonants, and changes in voice quality. Speech-language pathologists (SLPs) work with patients with PD to improve speech intelligibility using various intensive in-clinic speech treatments. SLPs also prescribe home exercises to enhance generalization of speech strategies outside of the treatment room. Even though speech therapies are found to be highly effective in improving vocal loudness and speech quality, patients with PD find it difficult to follow the prescribed exercise regimes outside the clinic and to continue exercises once the treatment is completed. SLPs need techniques to monitor compliance and accuracy of their patients\u27 exercises at home and in ecologically valid communication situations. We have designed EchoWear, a smartwatch-based system, to remotely monitor speech and voice exercises as prescribed by SLPs. We conducted a study of 6 individuals; three with PD and three healthy controls. To assess the performance of EchoWear technology compared with high-quality audio equipment obtained in a speech laboratory. Our preliminary analysis shows promising outcomes for using EchoWear in speech therapies for people with PD

Smart homes for the elderly of rural Oklahoma: A strategy for ethical implementation

Smart homes, telemedicine, and robots are often proposed as solutions to the upcoming problem of providing care to millions of older adults. The number of elderly in need of care has risen substantially, the number of available caretakers has not kept pace with demand, and this disparity will only increase as the Baby Boomer generation ages. The care of the elderly, which results in dependency on their part, conflicts with the strong individualism of American society, sometimes causing difficulties between the patient and caretaker(s) when making care decisions. Thus, many ethical concerns have been voiced about smart home technology, from privacy issues to fears of isolation (Fritz, 2015). These concerns vary based on the cultural background of the elderly user, with upper-middle class users feeling more comfortable with the technology (Fritz, 2015). Rural users, who are most in need of the technology due to having fewer nearby healthcare providers, and dementia users, who are in need of the technology to help manage their illness during the early stages while living at home, are the ones who tend to distrust the technology the most (Fritz, 2015). Smart home implementation for the elderly has progressed rapidly in recent years, but research has fallen behind in the sense of connecting theory and practice (Berridge, 2018). As a way to address this, the author proposes a study with researchers in the Dept. of Telemedicine at the OSU Medical School in Tulsa of the rural elderly in Oklahoma, since Oklahoma has approved insurance reimbursement for telemedicine, that would be expanded to include assistive technologies for smart homes in order to try to develop a participatory model for the ethical diffusion of this technology on a mass level

A simulator to support machine learning-based wearable fall detection systems

People’s life expectancy is increasing, resulting in a growing elderly population. That population is subject to dependency issues, falls being a problematic one due to the associated health complications. Some projects are trying to enhance the independence of elderly people by monitoring their status, typically by means of wearable devices. These devices often feature Machine Learning (ML) algorithms for fall detection using accelerometers. However, the software deployed often lacks reliable data for the models’ training. To overcome such an issue, we have developed a publicly available fall simulator capable of recreating accelerometer fall samples of two of the most common types of falls: syncope and forward. Those simulated samples are like real falls recorded using real accelerometers in order to use them later as input for ML applications. To validate our approach, we have used different classifiers over both simulated falls and data from two public datasets based on real data. Our tests show that the fall simulator achieves a high accuracy for generating accelerometer data from a fall, allowing to create larger datasets for training fall detection software in wearable devices.Junta de Comunidades de Castilla-La ManchaComunidad de MadridMinisterio de Ciencia e Innovació