Digital Twins for Health: Opportunities, Barriers and a Path Forward

The concept of precision medicine involves tailoring medical interventions to each patient’s specific needs, considering factors such as their genetic makeup, lifestyle, environment and response to therapies. The emergence of digital twin (DT) technology is anticipated to enable such customization. The healthcare field is, thus, increasingly exploring the use of digital twins (DTs), benefiting from successful proof of concept demonstrated in various industries. If their full potential is realized, DTs have the capability to revolutionize connected care and reshape the management of lifestyle, health, wellness and chronic diseases in the future. However, the realization of DTs’ full potential in healthcare is currently impeded by technical, regulatory and ethical challenges. In this chapter, we map the current applications of DTs in healthcare, with a primary focus on precision medicine. We also explore their potential applications in clinical trial design and hospital operations. We identify the key enablers of DTs in healthcare and discuss the opportunities and barriers that foster or hinder their larger and faster diffusion. By providing a comprehensive view of the current landscape, opportunities and challenges, we aim to contribute to DTs’ ongoing development and help policymakers facilitate the growth of DTs’ application in healthcare

Emerging Trends in Digital Health and Care : A Refresh Post-COVID

In the lead up to the pandemic, the implementation and use of digital health solutions and awareness of the field were steadily on the rise. However, the onset of the COVID-19 pandemic saw an unprecedented hike in the provision and the use of digital health and care solutions. This was a direct response of the health and care services globally to the various national lockdown measures implemented at the time. While such high levels of use of digital tech in health and care delivery are expected to fall post pandemic, the levels will remain much higher than those observed before the pandemic. This pandemic-accelerated proliferation of digital health and care solutions predictably pushed the sector onto the world stage, as the underlying infrastructures, legislation and guidance for these solutions needed to be realised. This report has been informed by large-scale desktop research of academic and grey literature, drawing information on post-COVID developments in digital health and care from international sources and across all levels of government, academia, business, and industry. The report begins with a looking at the enablers and drivers affecting the digitalisation of health and care, followed by a digital health and care market overview. After this, the report is organised into two parts: Part 1 reviews the various technical developments and Part 2 examines softer developments in digital health and care post-COVID. These developments are presented under overarching themes of the transformation of health and care services, migration from analogue and legacy systems to modern digital approaches, the acceleration of digital innovation in health and care, and the acceptance of digital in health and care. The primary takeaway from this review of the emerging trends in digital health and care is that there is now an established acceptance for digital health and care solutions as part of health and care service delivery. The pandemic has acted as a catalyst for change in the sector, with citizens expecting digital technology to play a part in the delivery of their health and care

Modelling human emotions using immersive virtual reality, physiological signals and behavioural responses

Tesis por compendio[ES] El uso de la realidad virtual (RV) se ha incrementado notablemente en la comunidad científica para la investigación del comportamiento humano. En particular, la RV inmersiva ha crecido debido a la democratización de las gafas de realidad virtual o head mounted displays (HMD), que ofrecen un alto rendimiento con una inversión económica. Uno de los campos que ha emergido con fuerza en la última década es el Affective Computing, que combina psicofisiología, informática, ingeniería biomédica e inteligencia artificial, desarrollando sistemas que puedan reconocer emociones automáticamente. Su progreso es especialmente importante en el campo de la investigación del comportamiento humano, debido al papel fundamental que las emociones juegan en muchos procesos psicológicos como la percepción, la toma de decisiones, la creatividad, la memoria y la interacción social. Muchos estudios se han centrado en intentar obtener una metodología fiable para evocar y automáticamente identificar estados emocionales, usando medidas fisiológicas objetivas y métodos de aprendizaje automático. Sin embargo, la mayoría de los estudios previos utilizan imágenes, audios o vídeos para generar los estados emocionales y, hasta donde llega nuestro conocimiento, ninguno de ellos ha desarrollado un sistema de reconocimiento emocional usando RV inmersiva. Aunque algunos trabajos anteriores sí analizan las respuestas fisiológicas en RV inmersivas, estos no presentan modelos de aprendizaje automático para procesamiento y clasificación automática de bioseñales. Además, un concepto crucial cuando se usa la RV en investigación del comportamiento humano es la validez: la capacidad de evocar respuestas similares en un entorno virtual a las evocadas por el espacio físico. Aunque algunos estudios previos han usado dimensiones psicológicas y cognitivas para comparar respuestas entre entornos reales y virtuales, las investigaciones que analizan respuestas fisiológicas o comportamentales están mucho menos extendidas. Según nuestros conocimientos, este es el primer trabajo que compara entornos físicos con su réplica en RV, empleando respuestas fisiológicas y algoritmos de aprendizaje automático y analizando la capacidad de la RV de transferir y extrapolar las conclusiones obtenidas al entorno real que se está simulando. El objetivo principal de la tesis es validar el uso de la RV inmersiva como una herramienta de estimulación emocional usando respuestas psicofisiológicas y comportamentales en combinación con algoritmos de aprendizaje automático, así como realizar una comparación directa entre un entorno real y virtual. Para ello, se ha desarrollado un protocolo experimental que incluye entornos emocionales 360º, un museo real y una virtualización 3D altamente realista del mismo museo. La tesis presenta novedosas contribuciones del uso de la RV inmersiva en la investigación del comportamiento humano, en particular en lo relativo al estudio de las emociones. Esta ayudará a aplicar metodologías a estímulos más realistas para evaluar entornos y situaciones de la vida diaria, superando las actuales limitaciones de la estimulación emocional que clásicamente ha incluido imágenes, audios o vídeos. Además, en ella se analiza la validez de la RV realizando una comparación directa usando una simulación altamente realista. Creemos que la RV inmersiva va a revolucionar los métodos de estimulación emocional en entornos de laboratorio. Además, su sinergia junto a las medidas fisiológicas y las técnicas de aprendizaje automático, impactarán transversalmente en muchas áreas de investigación como la arquitectura, la salud, la evaluación psicológica, el entrenamiento, la educación, la conducción o el marketing, abriendo un nuevo horizonte de oportunidades para la comunidad científica. La presente tesis espera contribuir a caminar en esa senda.[EN] In recent years the scientific community has significantly increased its use of virtual reality (VR) technologies in human behaviour research. In particular, the use of immersive VR has grown due to the introduction of affordable, high performance head mounted displays (HMDs). Among the fields that has strongly emerged in the last decade is affective computing, which combines psychophysiology, computer science, biomedical engineering and artificial intelligence in the development of systems that can automatically recognize emotions. The progress of affective computing is especially important in human behaviour research due to the central role that emotions play in many background processes, such as perception, decision-making, creativity, memory and social interaction. Several studies have tried to develop a reliable methodology to evoke and automatically identify emotional states using objective physiological measures and machine learning methods. However, the majority of previous studies used images, audio or video to elicit emotional statements; to the best of our knowledge, no previous research has developed an emotion recognition system using immersive VR. Although some previous studies analysed physiological responses in immersive VR, they did not use machine learning techniques for biosignal processing and classification. Moreover, a crucial concept when using VR for human behaviour research is validity: the capacity to evoke a response from the user in a simulated environment similar to the response that might be evoked in a physical environment. Although some previous studies have used psychological and cognitive dimensions to compare responses in real and virtual environments, few have extended this research to analyse physiological or behavioural responses. Moreover, to our knowledge, this is the first study to compare VR scenarios with their real-world equivalents using physiological measures coupled with machine learning algorithms, and to analyse the ability of VR to transfer and extrapolate insights obtained from VR environments to real environments. The main objective of this thesis is, using psycho-physiological and behavioural responses in combination with machine learning methods, and by performing a direct comparison between a real and virtual environment, to validate immersive VR as an emotion elicitation tool. To do so we develop an experimental protocol involving emotional 360º environments, an art exhibition in a real museum, and a highly-realistic 3D virtualization of the same art exhibition. This thesis provides novel contributions to the use of immersive VR in human behaviour research, particularly in relation to emotions. VR can help in the application of methodologies designed to present more realistic stimuli in the assessment of daily-life environments and situations, thus overcoming the current limitations of affective elicitation, which classically uses images, audio and video. Moreover, it analyses the validity of VR by performing a direct comparison using highly-realistic simulation. We believe that immersive VR will revolutionize laboratory-based emotion elicitation methods. Moreover, its synergy with physiological measurement and machine learning techniques will impact transversely in many other research areas, such as architecture, health, assessment, training, education, driving and marketing, and thus open new opportunities for the scientific community. The present dissertation aims to contribute to this progress.[CA] L'ús de la realitat virtual (RV) s'ha incrementat notablement en la comunitat científica per a la recerca del comportament humà. En particular, la RV immersiva ha crescut a causa de la democratització de les ulleres de realitat virtual o head mounted displays (HMD), que ofereixen un alt rendiment amb una reduïda inversió econòmica. Un dels camps que ha emergit amb força en l'última dècada és el Affective Computing, que combina psicofisiologia, informàtica, enginyeria biomèdica i intel·ligència artificial, desenvolupant sistemes que puguen reconéixer emocions automàticament. El seu progrés és especialment important en el camp de la recerca del comportament humà, a causa del paper fonamental que les emocions juguen en molts processos psicològics com la percepció, la presa de decisions, la creativitat, la memòria i la interacció social. Molts estudis s'han centrat en intentar obtenir una metodologia fiable per a evocar i automàticament identificar estats emocionals, utilitzant mesures fisiològiques objectives i mètodes d'aprenentatge automàtic. No obstant això, la major part dels estudis previs utilitzen imatges, àudios o vídeos per a generar els estats emocionals i, fins on arriba el nostre coneixement, cap d'ells ha desenvolupat un sistema de reconeixement emocional mitjançant l'ús de la RV immersiva. Encara que alguns treballs anteriors sí que analitzen les respostes fisiològiques en RV immersives, aquests no presenten models d'aprenentatge automàtic per a processament i classificació automàtica de biosenyals. A més, un concepte crucial quan s'utilitza la RV en la recerca del comportament humà és la validesa: la capacitat d'evocar respostes similars en un entorn virtual a les evocades per l'espai físic. Encara que alguns estudis previs han utilitzat dimensions psicològiques i cognitives per a comparar respostes entre entorns reals i virtuals, les recerques que analitzen respostes fisiològiques o comportamentals estan molt menys esteses. Segons els nostres coneixements, aquest és el primer treball que compara entorns físics amb la seua rèplica en RV, emprant respostes fisiològiques i algorismes d'aprenentatge automàtic i analitzant la capacitat de la RV de transferir i extrapolar les conclusions obtingudes a l'entorn real que s'està simulant. L'objectiu principal de la tesi és validar l'ús de la RV immersiva com una eina d'estimulació emocional usant respostes psicofisiològiques i comportamentals en combinació amb algorismes d'aprenentatge automàtic, així com realitzar una comparació directa entre un entorn real i virtual. Per a això, s'ha desenvolupat un protocol experimental que inclou entorns emocionals 360º, un museu real i una virtualització 3D altament realista del mateix museu. La tesi presenta noves contribucions de l'ús de la RV immersiva en la recerca del comportament humà, en particular quant a l'estudi de les emocions. Aquesta ajudarà a aplicar metodologies a estímuls més realistes per a avaluar entorns i situacions de la vida diària, superant les actuals limitacions de l'estimulació emocional que clàssicament ha inclòs imatges, àudios o vídeos. A més, en ella s'analitza la validesa de la RV realitzant una comparació directa usant una simulació altament realista. Creiem que la RV immersiva revolucionarà els mètodes d'estimulació emocional en entorns de laboratori. A més, la seua sinergia al costat de les mesures fisiològiques i les tècniques d'aprenentatge automàtic, impactaran transversalment en moltes àrees de recerca com l'arquitectura, la salut, l'avaluació psicològica, l'entrenament, l'educació, la conducció o el màrqueting, obrint un nou horitzó d'oportunitats per a la comunitat científica. La present tesi espera contribuir a caminar en aquesta senda.Marín Morales, J. (2020). Modelling human emotions using immersive virtual reality, physiological signals and behavioural responses [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/148717TESISCompendi

Networking Architecture and Key Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey

Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only virtually replicate a system's detailed operations but also analyze the current condition, predict future behaviour, and refine the control optimization. Although DT has been widely implemented in various fields, such as smart manufacturing and transportation, its conventional paradigm is limited to embody non-living entities, e.g., robots and vehicles. When adopted in human-centric systems, a novel concept, called human digital twin (HDT) has thus been proposed. Particularly, HDT allows in silico representation of individual human body with the ability to dynamically reflect molecular status, physiological status, emotional and psychological status, as well as lifestyle evolutions. These prompt the expected application of HDT in personalized healthcare (PH), which can facilitate remote monitoring, diagnosis, prescription, surgery and rehabilitation. However, despite the large potential, HDT faces substantial research challenges in different aspects, and becomes an increasingly popular topic recently. In this survey, with a specific focus on the networking architecture and key technologies for HDT in PH applications, we first discuss the differences between HDT and conventional DTs, followed by the universal framework and essential functions of HDT. We then analyze its design requirements and challenges in PH applications. After that, we provide an overview of the networking architecture of HDT, including data acquisition layer, data communication layer, computation layer, data management layer and data analysis and decision making layer. Besides reviewing the key technologies for implementing such networking architecture in detail, we conclude this survey by presenting future research directions of HDT

Interactive Three-Dimensional Simulation and Visualisation of Real Time Blood Flow in Vascular Networks

One of the challenges in cardiovascular disease management is the clinical decision-making process. When a clinician is dealing with complex and uncertain situations, the decision on whether or how to intervene is made based upon distinct information from diverse sources. There are several variables that can affect how the vascular system responds to treatment. These include: the extent of the damage and scarring, the efficiency of blood flow remodelling, and any associated pathology. Moreover, the effect of an intervention may lead to further unforeseen complications (e.g. another stenosis may be “hidden” further along the vessel). Currently, there is no tool for predicting or exploring such scenarios. This thesis explores the development of a highly adaptive real-time simulation of blood flow that considers patient specific data and clinician interaction. The simulation should model blood realistically, accurately, and through complex vascular networks in real-time. Developing robust flow scenarios that can be incorporated into the decision and planning medical tool set. The focus will be on specific regions of the anatomy, where accuracy is of the utmost importance and the flow can develop into specific patterns, with the aim of better understanding their condition and predicting factors of their future evolution. Results from the validation of the simulation showed promising comparisons with the literature and demonstrated a viability for clinical use

The role of artificial intelligence in surgical simulation

Artificial Intelligence (AI) plays an integral role in enhancing the quality of surgical simulation, which is increasingly becoming a popular tool for enriching the training experience of a surgeon. This spans the spectrum from facilitating preoperative planning, to intraoperative visualisation and guidance, ultimately with the aim of improving patient safety. Although arguably still in its early stages of widespread clinical application, AI technology enables personal evaluation and provides personalised feedback in surgical training simulations. Several forms of surgical visualisation technologies currently in use for anatomical education and presurgical assessment rely on different AI algorithms. However, while it is promising to see clinical examples and technological reports attesting to the efficacy of AI-supported surgical simulators, barriers to wide-spread commercialisation of such devices and software remain complex and multifactorial. High implementation and production costs, scarcity of reports evidencing the superiority of such technology, and intrinsic technological limitations remain at the forefront. As AI technology is key to driving the future of surgical simulation, this paper will review the literature delineating its current state, challenges, and prospects. In addition, a consolidated list of FDA/CE approved AI-powered medical devices for surgical simulation is presented, in order to shed light on the existing gap between academic achievements and the universal commercialisation of AI-enabled simulators. We call for further clinical assessment of AI-supported surgical simulators to support novel regulatory body approved devices and usher surgery into a new era of surgical education

A personalised emotion-based model for relaxation in virtual reality

One of the most frequent health problems is stress. It has been linked to negative effects on employee well-being in many occupations, and it is considered responsible for many physical and psychological problems. Traditional in-person relaxation therapy has proven to be effective in reducing stress. However, it has some drawbacks such as high cost, required infrastructure and the need for qualified trainers. Relaxation therapy in Virtual Reality (VR) tries to solve these problems. However, one aspect has received little attention, that is personalised therapy. Indeed, while many studies show the need for patient-tailored relaxation exercises, little existing work focuses on personalised VR content. One reason for this is the complexity of recognising emotions, which is required for emotion-based adaptive VR. In this work, a method for adapting VR content to the emotional state of the user is presented. This model has been applied in a VR relaxation therapy application, which adapts to the user's emotional state utilising a heuristic optimiser. Simulations have proven the performance and usability of the emotion model. Additionally, this paper explores the impact of the order in which adaptations are performed on the effectiveness of the relaxation experience

Anxiety activating virtual environments for investigating social phobias

Social phobia has become one of the commonest manifestations of fear in any society. This fear is often accompanied by major depression or social disabilities. With the awareness that fear can be aggravated in social situations, virtual reality researchers and psychologists have investigated the feasibility of a virtual reality system as a psychotherapeutic intervention to combat social phobia. Virtual reality technology has rapidly improved over the past few years, making for better interactions. Nevertheless, the field of virtual reality exposure therapy for social phobia is still in its infancy and various issues have yet to be resolved or event uncovered. The key concept of virtual reality exposure therapy in the treatment of social phobia is based on its characteristic of perceptual illusion - the sense of presence - as an anxiety-activating system, instead of conventional imaginal or in-vivo exposure techniques. Therefore, in order to provoke a significant level of anxiety in virtual environments, it is very important to understand the impact of perceptual presence factors in virtual reality exposure therapy. Hence, this research mainly aims to investigate all the aspects of the correlation between anxiety and the components of the virtual environment in a computer-generated social simulation. By understanding this, this thesis aims to provide a framework for the construction of effective virtual reality exposure therapy for social phobia care which enables anxiety stimuli to be controlled in a gradual manner as a conventional clinical approach. This thesis presents a series of experimental studies that have been conducted with a common theme: the function of 3D inhabitants and visual apparatus in anxiety-activating virtual social simulation, a job-interview. However, each study is conducted using different research objectives. The experimental results are presented in this thesis, with psycho-physiological approach, revealing a variation of the distribution of participants' anxiety states across various VR conditions. The overall conclusion of this research is that an appropriate realism of VR stimuli is essential in sustaining the state of anxiety over the course of VR exposure. The high fidelity of virtual environment generally provoke a greater degree of anxiety, but this research also shows that aspects of VR fidelity is more related to the mental representation of individuals to the context of the stressful situation rather than any technology that is being used

11th International Conference on Business, Technology and Innovation 2022

Welcome to IC – UBT 2022 UBT Annual International Conference is the 11th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make them be aware of the recent advancements in different research fields, and provide them with a unique forum to share their experiences. It is also the place to support the new academic staff for doing research and publish their work in international standard level. This conference consists of sub conferences in different fields like: Security Studies Sport, Health and Society Psychology Political Science Pharmaceutical and Natural Sciences Mechatronics, System Engineering and Robotics Medicine and Nursing Modern Music, Digital Production and Management Management, Business and Economics Language and Culture Law Journalism, Media and Communication Information Systems and Security Integrated Design Energy Efficiency Engineering Education and Development Dental Sciences Computer Science and Communication Engineering Civil Engineering, Infrastructure and Environment Architecture and Spatial Planning Agriculture, Food Science and Technology Art and Digital Media This conference is the major scientific event of the UBT. It is organizing annually and always in cooperation with the partner universities from the region and Europe. We have to thank all Authors, partners, sponsors and also the conference organizing team making this event a real international scientific event. Edmond Hajrizi, President of UBT UBT – Higher Education Institutio