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

Remote Teleassessment and Telerehabilitation of a Comprehensive Exercise Training Protocol for Older Adults: Design and Methodology of a Usability Protocol

ABSTRACT Purpose: The design, usability, safety, and feasibility of a telehealth protocol comprising teleassessment and tele rehabilitation to evaluate and improve physical and cognitive function among older adults was assessed. Methods: Healthy older adults (n=23) participated in a pre-post tele-assessment of a 4-week (3 sessions/week) telerehabilitation session. Tele-assessment was performed to evaluate balance, gait function, and cognition. Tele-rehabilitation sessions comprised of balance games, dancing, dual-tasking, yoga, and tai-chi exercises. Results: There were no adverse events reported to indicate concerns with the safety of the current telehealth protocol. Conclusion: The proposed telehealth protocol to assess and improve physical and cognitive function may be feasible for enrolling older adults into a home exercise trial

Information and communication technology-based interventions for chronic diseases consultation: Scoping review

Background: Medical consultations are often critical meetings between patients and health personnel to provide treatment, health-management advice, and exchange of information, especially for people living with chronic diseases. The adoption of patient-operated Information and Communication Technologies (ICTs) allows the patients to actively participate in their consultation and treatment. The consultation can be divided into three different phases: before, during, and after the meeting. The difference is identified by the activities in preparation (before), the meeting, conducted either physically or in other forms of non-face-to-face interaction (during), and the follow-up activities after the meeting (after). Consultations can be supported by various ICT-based interventions, often referred to as eHealth, mHealth, telehealth, or telemedicine. Nevertheless, the use of ICTs in healthcare settings is often accompanied by security and privacy challenges due to the sensitive nature of health information and the regulatory requirements associated with storing and processing sensitive information. Objective: This scoping review aims to map the existing knowledge and identify gaps in research about ICT-based interventions for chronic diseases consultations. The review objective is guided by three research questions: (1) which ICTs are used by people with chronic diseases, health personnel, and others before, during, and after consultations; (2) which type of information is managed by these ICTs; and (3) how are security and privacy issues addressed? Methods: We performed a literature search in ACM, IEEE, PubMed, Scopus, and Web of Science and included primary studies published between January 2015 and June 2020 that used ICT before, during, and/or after a consultation for chronic diseases. This review presents and discusses the findings from the included publications structured around the three research questions. Results: Twenty-four studies met the inclusion criteria. Only five studies reported the use of ICTs in all three phases: before, during, and after consultations. The main ICTs identified were smartphone applications, webbased portals, cloud-based infrastructures, and electronic health record systems. Different devices like sensors and wearable devices were used in 23 studies to gather diverse information. Regarding the type of information managed by these ICTs, we identified nine categories: physiological data, treatment information, medical history, consultation media like images or videos, laboratory results, reminders, lifestyle parameters, symptoms, and patient identification. Security issues were addressed in 20 studies, while only eight of the included studies addressed privacy issues. Conclusions: This scoping review highlights the potential for a new model of consultation for patients with chronic diseases. Furthermore, it emphasizes the possibilities for consultations besides physical and remote meetings

Closing the Loop for Patients with Chronic Diseases - from Problems to a Solution Architecture

There is growing evidence that mobile health (mHealth) applications can assist patients with chronic conditions. However, most mHealth apps are isolated from healthcare professional (HCP) workflows and IT infrastructure. The resulting fragmentation of digital support in healthcare calls for integrating architectures. They would benefit patients, HCPs, product managers, and software developers. Our analysis of existing architectures has revealed valuable architectural elements, but none of the analyzed architectures provided sufficient integration for the chronically ill. Therefore, we propose an architecture for integrated mHealth solutions. We followed a design science research approach and performed all activities of the DSRM Process Model. By forming a closed control loop and engaging HCPs, the architecture is designed to improve patient adherence to treatment, health literacy, and recall of recommendations and information. The resulting Closing-the-Loop Architecture (LoopArt) deploys three software agents: a Health Literacy Agent, an Adherence Agent, and a Conversational Agent. For demonstration purposes, the Health Literacy Agent was implemented for obese patients as an integrated system consisting of a mHealth app and a collaboration tool as part of the electronic medical record (EMR)

Internet of Things: Architecture and Services for Healthcare

Internet of Things (IoT) is a recent prominent collaboration of various technologies that enables spatially distributed devices (“things”) to sense, communicate and share information, thus generating a variety of applications and services in Healthcare. IoT is implemented in multiple domains like Smart city, energy and smart grid, Smart home, weather forecasting, Agriculture, Market and Transportation, Manufacturing and testing industries, Healthcare and many more. IoT serves the purpose of making tasks more efficient and productive and at the same time ensuring quality and reliability. IoT technologies provide an enabling framework for inter-connecting devices, systems, and services that go beyond Machine-to-Machine scenarios within today’s internet infrastructure. Healthcare industry is among the fastest fields to embrace IoT for numerous health services. IoT technologies will enable doctors / physicians / caretakers to be in touch with patients all the time. Various physiological parameters and markers can be monitored on a real-time basis for early detection of serious health symptoms that could endanger the life of patients. Diagnosis of diseases can be more accurate and in time for early treatment which will significantly improve recovery time. Diagnostic medical devices, sensors, and imaging devices that are integrated within the network for building an efficient and real-time system. The market for IoT in the healthcare sector is expected to grow rapidly in terms of connecting hospitals with patients for remote monitoring, emergency care services and remote surgery through augmented virtual reality. This thesis explores advances in IoT- based technologies in the healthcare environment. The thesis presents an architecture that defines a possible reference platform for seamless inter-connectivity between devices and software systems to enable new services. The architecture has multiple layers each of which performs specific functions to enable the realization of novel healthcare services. The thesis provides a comprehensive comparison between different Short range communication technologies, Mobile communication and Low Power Wide Area (LPWA) technologies. Based upon different scenarios of IoT healthcare services implementation, data computation capabilities provided by various cloud computing models and edge computing models are also discussed. The thesis provides a survey on various healthcare services that are implemented inside (and outside) hospital premises, e.g., remote health monitoring, Ambient Assisted Living among others. The impact of two prominent key technologies: Network Functions Virtualization (NFV) and Software Defined Networks (SDN) has been discussed and showed the benefits of implementing control and management function-especially at the edge network- utilizing SDN/NFV. This provides a flexible approach for deployment of healthcare services in close proximity to computing resources and improves communication control. IoT acknowledges a reliable and secure data exchange in real-time and oriented to improve Quality of Life (QoL). Internet of Things (IoT) serves the purpose of the advance concatenation of devices, systems, and services that go beyond the Machine-to-Machine scenario within today’s internet infrastructure with extended benefits

Sistema inteligente de decisión ubicuo para la monitorización de pacientes con cardiopatía isquémica

Los programas de prevención secundaria y rehabilitación cardíaca han demostrado reducir la morbimortalidad en las enfermedades cardiovasculares. Sin embargo, el porcentaje de pacientes que acceden es muy bajo en nuestro entorno. Entre las causas de falta de accesibilidad, se encuentran causas tanto de índole sociodemográfico-cultural como la carencia de atención individualizada. La propuesta de esta tesis doctoral es presentar un Sistema de Decisión Inteligente Ubicuo denominado RED-Core con pulseras vestibles basado en técnicas de soft computing, orientado al programa de rehabilitación cardíaca domiciliaria.Secondary prevention and cardiac rehabilitation programs have been shown to reduce morbidity and mortality in cardiovascular diseases. However, the percentage of patients who access is very low in our environment. Among the causes of lack of accessibility, there are causes of both sociodemographic-cultural nature and lack of individualized attention. The proposal of this doctoral thesis is to present a Ubiquitous Decision Intelligent System with wearable bracelets based on soft computing techniques, oriented to the home cardiac rehabilitation program.Tesis Univ. Jaén. Departamento de Informática. Leída el 4 de mayo de 2020

A Two-Part Study of Step Counter Accuracy and Ecological Momentary Assessment of Correlates to Total Physical Activity in Phase II Cardiac Rehabilitation Patients

Cardiac rehabilitation (CR) is an exercise and education program aimed to help individuals improve fitness levels to return to their careers and social lives. The dropout rate is high, between 25% to 50%, and is related to several factors with an early predictor being higher anxiety levels. It is important to understand the patterns and consistency of this variable as it changes throughout the day and its association physical activity (PA) in order to influence interventions. Ecological momentary assessment (EMA) and actigraphy can capture momentary anxiety and PA, respectively, for temporal analysis. This dissertation includes two studies. Study I examined the error in daily steps of four wearable PA monitors (Fitbit Charge 2, Apple Watch Series 2, Fitbit Zip, ActiGraph GT9X) in phase II CR patients. Nineteen patients wore activity monitors on the ankle, non-dominant wrist, and waist on two days that they attended CR and two days when they did not. Steps from each monitor were compared to criterion steps from the StepWatch (SW). The Fitbit Charge and Apple Watch captured within 10% of SW steps and most other monitors underestimated steps. Study II examined the consistency and intra- and inter-individual patterns in state anxiety (SA) and PA and described the feasibility of mobile EMA for those in phase II CR. Nine adults received four mobile phone surveys each day, assessing momentary SA, for 14 consecutive days while concurrently wearing an ActiGraph GT3X+ across the day. In this study, participants demonstrated consistent, low levels of SA (ICC = 0.68, average = 9.1 on a scale of 6 to 24). The relationship between PA and SA varied between individuals, showing positive and negative slopes for individual participants. Survey compliance rate and ActiGraph wear time met a priori benchmarks for feasibility, but recruitment did not. Lack of smartphone ownership and limited smartphone access at work were the primary challenges to recruitment. This study was the first to describe the patterns of momentary SA for this population. Individual pattern analysis is necessary for classifying individuals, but further study is needed to direct development of interventions based on ecologically valid data

Dia-Continua: An Information System for Type 1 Diabetes Consultation. (Interoperability, Privacy, and Information Quality on a FHIR-Based Information System for Type 1 Diabetes Consultations based on Patient-Generated Health Data)

Patient-generated health data (PGHD) is required to monitor chronic conditions like Type 1 Diabetes (T1D). This data includes information from medical devices like insulin pumps and continuous glucose monitors and lifestyle insights from commercial wearables devices such as smartwatches. To improve the quality of medical consultations, we need a unified information system that can integrate PGHD. Designing such a system will pose several challenges. The system should be able to navigate through fragmented information and the complexities of various data formats, proprietary interfaces, and storage methods while ensuring robust security, privacy, and adherence to data ownership principles. It should also enable controlled data sharing with healthcare providers (HCPs) and external entities such as national registries and informal caregivers. This dissertation details designing, developing, and testing an information system for individuals with T1D. The project involved integrative research in health informatics, collaboration with international projects, and collaboration with experienced users and HCPs to address three research questions. These questions focused on interoperability, the security and privacy of the information collected, and the quality of the information presented during consultations. The result is Dia-Continua, a Fast Healthcare Interoperability Resources (FHIR)-based information system with a microservices architecture orchestrated through Kubernetes on an Infrastructure as a Service (IaaS) platform. The system integrates data from various diabetes management devices, questionnaires, and PGHD. Furthermore, using SMART on FHIR for authorization and authentication enables data sharing and reuse with national registries and informal caregivers. Eleven interviews with HCPs evaluated Dia-Continua's new functionalities and information quality. Despite the limitations due to proprietary device systems, the system was assessed positively by HCPs, highlighting the need for a system like Dia-Continua that includes physical activity, sleep, and stress in medical consultations. Dia-Continua is a significant step for a patient-centred model for consultations in T1D. Future work should expand the system's model to other chronic diseases.Utviklingen av medisinske konsultasjoner for kroniske tilstander, spesifikt Type 1 Diabetes (T1D), avhenger i stor grad av pasientgenererte helsedata (PGHD). Disse dataene inkluderer informasjon fra medisinsk utstyr slik som insulinpumper, CGM, samt livsstils data fra kommersielt utstyr som sensorer på smartklokker og smarte ringer. Et helhetlig informasjonssystem som kan integrere PGHD er nødvendig for å forbedre informasjonskvalitet under medisinske konsultasjoner. Imidlertid bør et slikt system være i stand til å la brukeren navigere gjennom fragmentert informasjon og komplekse heterogene dataformater, proprietære grensesnitt og lagringsmetoder, samtidig som systemet sikrer robust sikkerhet, personvern og ivaretakelse av prinsipper for eierskap til data. Systemet bør også muliggjøre kontrollert deling av data med helsepersonell og eksterne aktører slik som nasjonale registre (Noklus) og pasientens omsorgspersoner. Denne avhandlingen beskriver design, utvikling, testing og evaluering av et nytt informasjonssystem for T1D basert på pasientens egne data. Prosjektet har involvert ulike samarbeidspartnere og profesjoner, samt samarbeid med internasjonale prosjekter, erfarne brukere og HP for å adressere de tre forskningsspørsmålene i prosjektet. Ett av resultatene er systemet Dia-Continua, et Fast Healthcare Interoperability Resources (FHIR)-basert informasjonssystem med en Microservice arkitektur orkestrert gjennom Kubernetes på en infrastruktur som en tjenesteplattform (Azure). Systemet integrerer data fra ulike diabetesenheter, spørreskjemaer og andre sensorer. Videre, ved å bruke «SMART on FHIR» for autorisasjon og autentisering, muliggjøres deling og gjenbruk av data med nasjonale registre og uformelle omsorgspersoner. Elleve intervjuer med helsepersonell ble gjort for å evaluere Dia-Continua sine nye funksjonaliteter, samt dets informasjonskvalitet. Til tross for begrensningene på grunn av proprietære standarder, ble systemet positivt mottatt av HP. Informantene understreket behovet for et system som Dia-Continua som inkluderer fysisk aktivitet, søvn og stress i medisinske konsultasjoner. Dia-Continua er et betydelig skritt fram mot en pasientsentrert modell for konsultasjoner i T1D. Fremtidig arbeid bør utvide systemets modell til andre kroniske sykdommer

An intelligent mHealth-based adjunct to improve the management of patients with cardiovascular disease

Regular recording of vital signs, modification of lifestyle behaviour and monitoring of health progress has been shown to be effective to better manage patients with cardiovascular disease (CVD). Despite this, there remain significant hospital readmissions due to CVD exacerbations. This thesis investigated if the readmission rate of CVD patients could be reduced through remote longitudinal monitoring of physiological measurements and by offering a mobile health (mHealth)-based adjunct to assist in lifestyle modification. The thesis also investigated if there was a relationship between patient engagement and their clinical outcomes. To improve the remote management of CVD patients, the architecture of an intelligent mHealth adjunct called Total Cardiac Care (TCC) was developed based around a smartphone app and wireless peripherals to record physiological data and patient activity. The system also enabled the clinician to regularly monitor the patients’ condition using a web portal, facilitating the timely interventions when deemed necessary. The proposed system feasibility was investigated in a pilot trial, where it was widely accepted by both younger and older CVD patients with a high satisfaction rate (89.5%). The participants also had a high engagement rate with the different monitoring features (BP 77.2%, weight 74.3% and activity 84.8%). The results of a randomised controlled trial in which CVD patients (n = 164) were randomly assigned to either the mHealth intervention group or a traditional care control group identified a significant reduction in the 6-month all-cause (21 vs 41, risk reduction 49%, p = 0.015) and cardiac readmission (11 vs 25, risk reduction 56%, p = 0.025) risk when comparing the intervention cohort against the control cohort. These results suggest that the mHealth adjunct could increase the CVD patient’s engagement and the monitoring of physiological measurements and activity along with modified lifestyle behaviour over the long term could improve their cardiac health and decrease adverse events. To predict the CVD patient’s exacerbation, a model capable of detecting worsening events based on the critical change in the longitudinal physiological trends was developed using telemonitoring data collected from the intervention cohort. The model correctly predicted the CVD exacerbation events with 86.4% sensitivity, 58.4% specificity and 59.7% accuracy. This highlights that the integration of an exacerbation prediction model with the mHealth adjunct could enhance the quality of remote monitoring care provided to CVD patients