Wearable Technology Supported Home Rehabilitation Services in Rural Areas:– Emphasis on Monitoring Structures and Activities of Functional Capacity Handbook

The sustainability of modern healthcare systems is under threat. – the ageing of the population, the prevalence of chronic disease and a need to focus on wellness and preventative health management, in parallel with the treatment of disease, pose significant social and economic challenges. The current economic situation has made these issues more acute. Across Europe, healthcare expenditure is expected to rice to almost 16% of GDP by 2020. (OECD Health Statistics 2018). Coupled with a shortage of qualified personnel, European nations are facing increasing challenges in their ability to provide better-integrated and sustainable health and social services. The focus is currently shifting from treatment in a care center to prevention and health promotion outside the care institute. Improvements in technology offers one solution to innovate health care and meet demand at a low cost. New technology has the potential to decrease the need for hospitals and health stations (Lankila et al., 2016. In the future the use of new technologies – including health technologies, sensor technologies, digital media, mobile technology etc. - and digital services will dramatically increase interaction between healthcare personnel and customers (Deloitte Center for Health Solutions, 2015a; Deloitte Center for Health Solutions 2015b). Introduction of technology is expected to drive a change in healthcare delivery models and the relationship between patients and healthcare providers. Applications of wearable sensors are the most promising technology to aid health and social care providers deliver safe, more efficient and cost-effective care as well as improving people’s ability to self-manage their health and wellbeing, alert healthcare professionals to changes in their condition and support adherence to prescribed interventions. (Tedesco et al., 2017; Majumder et al., 2017). While it is true that wearable technology can change how healthcare is monitored and delivered, it is necessary to consider a few things when working towards the successful implementation of this new shift in health care. It raises challenges for the healthcare systems in how to implement these new technologies, and how the growing amount of information in clinical practice, integrates into the clinical workflows of healthcare providers. Future challenges for healthcare include how to use the developing technology in a way that will bring added value to healthcare professionals, healthcare organizations and patients without increasing the workload and cost of the healthcare services. For wearable technology developers, the challenge will be to develop solutions that can be easily integrated and used by healthcare professionals considering the existing constraints. This handbook summarizes key findings from clinical and laboratory-controlled demonstrator trials regarding wearables to assist rehabilitation professionals, who are planning the use of wearable sensors in rehabilitation processes. The handbook can also be used by those developing wearable sensor systems for clinical work and especially for use in hometype environments with specific emphasis on elderly patients, who are our major health care consumers

A Microservices e-Health System for Ecological Frailty Assessment Using Wearables

The population in developed countries is aging and this fact results in high elderly health costs, as well as a decrease in the number of active working members to support these costs. This could lead to a collapse of the current systems. One of the first insights of the decline in elderly people is frailty, which could be decelerated if it is detected at an early stage. Nowadays, health professionals measure frailty manually through questionnaires and tests of strength or gait focused on the physical dimension. Sensors are increasingly used to measure and monitor different e-health indicators while the user is performing Basic Activities of Daily Life (BADL). In this paper, we present a system based on microservices architecture, which collects sensory data while the older adults perform Instrumental ADLs (IADLs) in combination with BADLs. IADLs involve physical dimension, but also cognitive and social dimensions. With the sensory data we built a machine learning model to assess frailty status which outperforms the previous works that only used BADLs. Our model is accurate, ecological, non-intrusive, flexible and can help health professionals to automatically detect frailty.Ministry of Economy and Competitiveness from Spain MINECO/FEDER MAT2017-85999PEuropean Union (EU) MINECO/FEDER MAT2017-85999PRegional Government of Andalusia Research Fund from Spain A-BIO-157-UGR-1

Early diagnosis of frailty: Technological and non-intrusive devices for clinical detection

This work analyses different concepts for frailty diagnosis based on affordable standard technology such as smartphones or wearable devices. The goal is to provide ideas that go beyond classical diagnostic tools such as magnetic resonance imaging or tomography, thus changing the paradigm; enabling the detection of frailty without expensive facilities, in an ecological way for both patients and medical staff and even with continuous monitoring. Fried's five-point phenotype model of frailty along with a model based on trials and several classical physical tests were used for device classification. This work provides a starting point for future researchers who will have to try to bridge the gap separating elderly people from technology and medical tests in order to provide feasible, accurate and affordable tools for frailty monitoring for a wide range of users.This work was sponsored by the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund (ERDF) across projects RTC-2017-6321-1 AEI/FEDER, UE, TEC2016-76021-C2-2-R AEI/FEDER, UE and PID2019-107270RB-C21/AEI/10.13039/501100011033, UE

Active aging : the role of mechanical exposure on functional capacity of the active population in the automotive industry

A presente tese teve por objetivo compreender às principais mudanças na capacidade funcional e na mobilidade dos trabalhadores seniores da indústria automóvel, afim de promover uma adaptação efetiva das condições do trabalho, tendo como aliada a capacidade funcional dos trabalhadores em suas diferentes faixas etárias, com destaque aqueles que pertencem ao grupo etário acima dos 40 anos. Os capítulo 2 e 3, respectivamente, tiveram como enfoque a interação entre as condições de trabalho e a capacidade funcional dos trabalhadores da indústria automóvel e a definição de perfis de capacidade funcional. Os resultados encontrados no capítulo 2 demonstraram que as exigências de força, altura e peso e a antiguidade na empresa, foram fatores preditivos para o declínio da capacidade funcional nos testes de Lifting Low, Lifting High e Handgrip. O resultado de destaque no capítulo 3 está no grupo etário dos 20-29 anos, com os menores valores referentes ao teste de capacidade funcional Handgrip e Overhead Working, em relação aos demais grupos etários. Tanto no capítulo 2 quanto no 3, a medida mais robusta dos testes de capacidade funcional, foi a medida Handgrip. No capítulo 4, foram definidos os valores normativos de força de preensão (Handgrip). Os resultados mais expressivos, deste capítulo, estão relacionados ao grupo das mulheres dos 30-34 anos, com um declínio significativo de 4 kg a menos de força de preensão, em comparação aos demais grupos etários. E no grupo dos homens o declínio ocorreu na faixa etário dos 40-57 anos, como esperado. Concluísse nesta presente tese que os trabalhadores seniores não demonstram declínios significativos da capacidade funcional.The present thesis aimed to understand the main changes in the functional capacity and mobility of senior workers in the automotive industry. To promote an active adaptation of work requirements, having as an ally the functional capacity of workers in their different age groups, with emphasis those belonging to the age group above 40 years. Chapters 2 and 3, respectively, focused on the interaction between working conditions and the functional capacity of workers in the automotive industry and the definition of functional capacity profiles. The results found in chapter 2, demonstrated that the strength (related to work requirements), height and weight and seniority in the company, were predictive factors for the decline in functional capacity in the Lifting Low, Lifting High, and Handgrip tests. The outstanding result in chapter 3 is in the 20-29 age group, with the lowest values referring to the Handgrip and Overhead Working Functional Capacity Test, concerning the other age groups. In both chapters 2 and 3, the most robust measure of functional capacity tests was the Handgrip measure. So, in chapter 4, defined normative values of grip strength (Handgrip). The most significant results in this chapter are related to the group of women aged 30-34 years, with a substantial decline of 4 kg less grip strength, compared to the other age groups. And in the male group, the decline occurred in the 40-57 age group, as expected. It is concluded in this thesis that the senior workers do not demonstrate significant declines in functional capacity

PUSHING THE BOUNDARIES OF CONSUMER GRADE WEARABLE DEVICES IN HEALTH CARE FOR OLDER ADULTS

Background: The proliferation of wearable and mobile devices in recent years has led to the generation of unprecedented amounts of health-related data. Together with the growing population of older adults in Canada, the increasing adoption of these technologies created a momentous opportunity to improve the way we deliver, access, and interact with the health care system. Many have recognized the opportunity, yet there is a lack of evidence on how these devices and the growing size of health data can be used to transform health care and benefit us. In Chapter 2, a review of the literature was presented to identify the current evidence of wearable technology and gaps that exist in aging research. Based on the literature review, one promising way to use wearable devices is to assess frailty, which can contribute to improving care and enhancing aging-in-place. Chapter 3 summarizes key concepts related to wearable devices including mobile health, patient-generated health data, big data, predictive algorithms, machine learning, and artificial intelligence. While in-depth mathematical representation of these big data analytics is outside the scope of this dissertation, this chapter provides foundational information along with examples found in health care settings. Objective: The overall aim of this dissertation was to investigate possible use of consumer-grade wearable devices and the patient-generated health data to improve the health of older adults. Methods: This thesis is presented as three individual studies included in Chapters 4 to 6. Study 1 aimed to investigate use of wearable devices to predict and find associations with frailty for community-dwelling older adults receiving home care service. Participants were asked to wear wearable device for 8 days in their home environment and no supervision was provided. Frailty level was assessed using the Fried Frailty Index. Other variables were collected including Charlson Comorbidity Index, independence using the Katz Index, and home care service utilization level. A sequential stepwise feature selection method was used to determine variables that are fitted in multiple variable logistic regression model to predict frailty. Study 2 extended the investigation of possible use of wearable devices for understanding frailty by examining the relationship between wearable device data and frailty progression among critical illness survivors from an intensive care unit at Kingston General Hospital. Participants were assessed for frailty using the Clinical Frailty Scale three times; at admission, at hospital discharge, and at 4-weeks post-hospital discharge. The changes in frailty level between the three time points were used to identify association with wearable device data that was collected for 4 weeks post-hospital discharge. Demonstrating evidence for wearable devices and patient-generated health data in research does not guarantee its use in real life. In Study 3, a mixed method study was conducted to explore clinicians’ and older adults’ perceptions of patient-generated health data. Focus group interviews were conducted with older adults and health care providers from the Greater Toronto Area and the Kitchener-Waterloo region. A questionnaire that aimed to explore perceived usefulness of a range of different patient-generated health data was embedded in the study design. Focus group interviews were transcribed verbatim. Line by line coding was conducted on all interviews followed by thematic analysis. Results: Results from Study 1 indicate data generated from wearable devices are closely linked to frailty level. Results showed a significant difference between frail and non-frail participants in age (p<0.01), home care service utilization (p=0.012), daily step count (p=0.04), total sleep time (p=0.010), and deep sleep time (p<0.01). Total sleep time (r=0.41, p=0.012) and deep sleep time (r=0.53, p<0.01) were associated with frailty level. A receiver operating characteristics area under the curve of 0.90 was achieved using deep sleep time, sleep quality, age, and education level (Hosmer-Lemeshow p=0.88), demonstrating that data from wearable devices can augment the demographic and conventional clinical data in predicting frailty status. Results from Study 2 demonstrated that frailty level increases significantly following a critical illness (p=0.02). Frail survivors had significantly lower daily step counts (p=0.02). Daily step count (r=-0.72, p=0.04) and mean heart rate (r=-0.72, p=0.046) were strongly correlated with frailty level at admission and discharge. Mean standard deviation of heart rate was correlated with the change in frailty status from admission to 4-week follow-up (r=0.78, p<0.05). The results demonstrated a relationship between the worsening of frailty due to critical illness and the pattern of increasing step count (r=0.65, p=0.03) and heart rate (r=0.62, p=0.03) over the 4-week observation period. Results from Study 3 provided an understanding of what older adults and clinicians considered barriers to using patient-generated health data in their care and clinical settings. Four main themes were identified from the focus group interviews: influence of patient-generated health data on patient-provider trust; reliability of patient-generated health data; meaningful use of patient-generated health data and decision support system; and perceived clinical benefits and intrusiveness of patient-generated health data. Results from the questionnaire and focus group interviews demonstrated that older adults and clinicians perceived blood glucose, step count, physical activity, sleep, blood pressure, and stress level as the most useful data for managing their health and delivering high quality care. Discussion: This dissertation provides evidence for using consumer-grade wearable device to assess, monitor, and predict frailty for older adults who receive home care or survived critical illness. The possibility of using a wearable device to assess frailty can enable health care providers to obtain frailty information in a timely manner, which is challenging to acquire otherwise due to a lack of appropriate tools in primary care, ambulatory care, home and community care, critical illness care, and other sectors. There was a distinct relationship between failure to recover frailty level from critical illness and the pattern of daily step count and heart rate. This can enable early detection of critical illness survivors who may not return to pre-critical illness level. It can provide guidance to identify those who may benefit the most from follow-up visits and elevated treatment. To ensure the benefits of patient-generated health data are realized, it must be integrated into health care. There are technical challenges that prevent such integration and discussion around policies and regulations must begin to make progress. Conclusion: This dissertation demonstrated use of wearable devices to assess frailty and identified factors that can hinder the integration of patient-generated health data into health care. It opened a possibility of assessing frailty, expanding the boundaries of current use of consumer-grade wearable devices

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

Enhanced Living Environments

This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area

Effect of Beers Criteria on Healthcare Utilization and Cost in Community-Dwelling Elderly Patients

This retrospective cohort study uses 2013 Marketscan® claims data to quantify healthcare resource utilization and national healthcare costs attributable to using potentially inappropriate medications represented in 2012 Beers Criteria. We compare hospital admissions, days spent in the hospital, and total healthcare costs generated from inpatient and outpatient visits and prescription medication use for community-dwelling Medicare patients that received medications in Beers Criteria compared to a well-matched group of patients that received medications not included in Beers Criteria. Using Beers Criteria medications is associated with greater odds of hospital admission. Of those that are hospitalized, patients using Beers Criteria medications experience a greater number of hospital admissions and spend more days in the hospital compared to patients treated with medications not in Beers Criteria. We found total inpatient, outpatient, and prescription drug costs to be higher on average for patients that received Beers Criteria medications, and these patients were responsible for significantly higher annual healthcare costs in 2013. This study suggests the importance reducing the risk of unnecessary hospitalizations attributed to using inappropriate medications to minimize the burden the elderly population will have on our national healthcare system in the future