Understanding Ambulatory and Wearable Data for Health and Wellness

In our research, we aim (1) to recognize human internal states and behaviors (stress level, mood and sleep behaviors etc), (2) to reveal which features in which data can work as predictors and (3) to use them for intervention. We collect multi-modal (physiological, behavioral, environmental, and social) ambulatory data using wearable sensors and mobile phones, combining with standardized questionnaires and data measured in the laboratory. In this paper, we introduce our approach and some of our projects

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

CoachAI: A Conversational Agent Assisted Health Coaching Platform

Poor lifestyle represents a health risk factor and is the leading cause of morbidity and chronic conditions. The impact of poor lifestyle can be significantly altered by individual behavior change. Although the current shift in healthcare towards a long lasting modifiable behavior, however, with increasing caregiver workload and individuals' continuous needs of care, there is a need to ease caregiver's work while ensuring continuous interaction with users. This paper describes the design and validation of CoachAI, a conversational agent assisted health coaching system to support health intervention delivery to individuals and groups. CoachAI instantiates a text based healthcare chatbot system that bridges the remote human coach and the users. This research provides three main contributions to the preventive healthcare and healthy lifestyle promotion: (1) it presents the conversational agent to aid the caregiver; (2) it aims to decrease caregiver's workload and enhance care given to users, by handling (automating) repetitive caregiver tasks; and (3) it presents a domain independent mobile health conversational agent for health intervention delivery. We will discuss our approach and analyze the results of a one month validation study on physical activity, healthy diet and stress management

On assumed usefulness of wearable sensors in early recognition of migraine attacks perceived by patients

This study analysed how migraine patients assume to improve their daily life if wearable sensors provide them pre-warnings of approaching or impending migraine attacks. The study analysed the use of new technology in identifying pre-symptoms in migraine patients using the Technology Acceptance Model (TAM) focusing on the assumed usefulness of a wearable device. The study added understanding of getting migraine patients to accept smart technology to support their own treatments. The results were drawn from a sample of altogether 582 migraine patients with or without an aura. The difference between migraine with aura and without aura is that migraine with aura precedes physical symptoms like visual disturbances, numbness, and difficulty in speech, while there are no pre-symptoms in migraine without aura. The assumed wearable device (WBAN) notifies, however, the bio-signals of an oncoming migraine attack. Due to current achievements with available digitalised tools to monitor health and wellbeing, also self-care is benefiting. Pre-migraine symptoms are among the biggest challenges in identifying migraine. Noting this, our study addressed the value of wearable sensors in early recognition of migraine attacks

Revisión del estado del arte sobre tendencias tecnológicas para el análisis del comportamiento y actividades humanas

The study of human behavior allows the knowledge about people's behaviors, behavior determined by multiple factors: cultural, social, psychological, genetic, religious, among others, which affect the relationships and interaction with the environment. The infinity of data in our lives and the search for behavioral patterns from that data has been an amazing work whose benefit is focused on the determined patterns and intelligent analysis that lead to new knowledge. A significant amount of resources from pattern recognition in human activities and daily life has had greater dominance in the management of mobility, health and wellness.The current paper presents a review of technologies for human behavior analysis and use as tools for diagnosis, assistance, for interaction in intelligent environments and assisted robotics applications. The main scope is to give an overview of the technological advances in the analysis of human behavior, activities of daily living and mobility, and the benefits obtained.El estudio del comportamiento humano permite el conocimiento sobre las conductas de las personas, conducta determinada por múltiples factores: culturales, sociales, psicológicos, genéticos, religiosos, entre otros; que inciden en las relaciones y la interacción con el entorno. La infinidad de datos en nuestras vidas y la búsqueda de patrones de comportamiento a partir de esos datos ha sido un trabajo asombroso cuyo provecho se centra en los patrones determinados y el análisis inteligente que conducen a nuevos conocimientos. Una cantidad significativa de recursos a partir del reconocimiento de patrones en las actividades humanas y de vida diaria ha tenido mayor dominio en la gestión de la movilidad, la salud y bienestar.El actual documento presenta una revisión de las tecnologías para el análisis del comportamiento humano y del uso como herramientas para el diagnóstico, asistencia, para la interacción en ambientes inteligentes y aplicaciones de robótica asistida. El alcance principal es dar una visión general de los avances tecnológicos en el análisis del comportamiento humano, actividades de la vida diaria y movilidad, y de los beneficios obtenidos

Hum Factors

Objective:To gather information on the (a) types of wearable sensors, particularly personal activity monitors, currently used by occupational safety and health (OSH) professionals, (b) potential benefits of using such technologies in the workplace, and (c) perceived barriers preventing the widespread adoption of wearable sensors in industry.Background:Wearable sensors are increasingly being promoted as a means to improve employee health and well-being and there is mounting evidence supporting their use as exposure assessment and personal health tools. Despite this, many workplaces have been hesitant to adopt these technologies.Methods:An electronic survey was emailed to 28,428 registered members of the American Society of Safety Engineers (ASSE) and 1,302 professionals certified by the Board of Certification in Professional Ergonomics (BCPE).Results:A total of 952 valid responses were returned. Over half of respondents described being in favor of using wearable sensors to track OSH-related risk factors and relevant exposure metrics at their respective workplaces. However, barriers including concerns regarding employee privacy/confidentiality of collected data, employee compliance, sensor durability, the cost/benefit ratio of using wearables, and good manufacturing practice requirements were described as challenges precluding adoption.Conclusion:The broad adoption of wearable technologies appears to depend largely on the scientific community\u2019s ability to successfully address the identified barriers.Application:Investigators may use the information provided to develop research studies that better address OSH practitioner concerns and that help technology developers operationalize wearable sensors to improve employee health and well-being.T42 OH008436/OH/NIOSH CDC HHSUnited States/2022-07-22T00:00:00Z29320232PMC930713011686vault:4300

Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions