Health State Estimation

Life's most valuable asset is health. Continuously understanding the state of our health and modeling how it evolves is essential if we wish to improve it. Given the opportunity that people live with more data about their life today than any other time in history, the challenge rests in interweaving this data with the growing body of knowledge to compute and model the health state of an individual continually. This dissertation presents an approach to build a personal model and dynamically estimate the health state of an individual by fusing multi-modal data and domain knowledge. The system is stitched together from four essential abstraction elements: 1. the events in our life, 2. the layers of our biological systems (from molecular to an organism), 3. the functional utilities that arise from biological underpinnings, and 4. how we interact with these utilities in the reality of daily life. Connecting these four elements via graph network blocks forms the backbone by which we instantiate a digital twin of an individual. Edges and nodes in this graph structure are then regularly updated with learning techniques as data is continuously digested. Experiments demonstrate the use of dense and heterogeneous real-world data from a variety of personal and environmental sensors to monitor individual cardiovascular health state. State estimation and individual modeling is the fundamental basis to depart from disease-oriented approaches to a total health continuum paradigm. Precision in predicting health requires understanding state trajectory. By encasing this estimation within a navigational approach, a systematic guidance framework can plan actions to transition a current state towards a desired one. This work concludes by presenting this framework of combining the health state and personal graph model to perpetually plan and assist us in living life towards our goals.Comment: Ph.D. Dissertation @ University of California, Irvin

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

Automatic Derivation of Requirements for Components Used in Human-Intensive Systems

Human-intensive systems (HISs), where humans must coordinate with each other along with software and/or hardware components to achieve system missions, are increasingly prevalent in safety-critical domains (e.g., healthcare). Such systems are often complex, involving aspects such as concurrency and exceptional situations. For these systems, it is often difficult but important to determine requirements for the individual components that are necessary to ensure the system requirements are satisfied. In this thesis, we investigated an approach that employs interface synthesis methods developed for software systems to automatically derive such requirements for components used in HISs. In previous work, we investigated a requirement deriver that employs a regular language learning algorithm to iteratively refine the derived requirement based on counterexamples generated by model checking techniques. Since this learning-based requirement deriver often did not scale well, we investigated several learning and model checking optimizations. These optimizations significantly improved performance but affected the counterexample generation heuristics, often widely varying the permissiveness of the derived requirements. For comparison purposes, we investigated a direct requirement deriver that was purported to have poor performance but guarantees the derived requirements are adequately permissive, conceptually meaning the requirements are permissive as possible without violating the system requirements. For our evaluation, we applied these requirement derivers to case studies in two important domains, healthcare and election administration. Based on this evaluation, the direct requirement deriver with all optimizations applied had reasonable performance and ensures the derived requirements are adequately permissive. For the learning-based requirement deriver, many of the optimizations and heuristics have been presented previously, but we recommend how to selectively combine them to obtain reasonable performance while usually producing the adequately permissive derived requirements. Since such derived requirements often reflect the system complexity, these requirements can be easily misunderstood. Thus, we also investigated building views of the requirements that abstract away or highlight certain aspects to try to improve their understandability. Each single view appears to improve understandability and the multiple views seem to complement each other further improving understandability. Such derived requirements and their views can be used to safely develop and deploy the components used in HISs

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Towards the Verification of Pervasive Systems

Pervasive systems, that is roughly speaking systems that can interact with their environment, are increasingly common. In such systems, there are many dimensions to assess: security and reliability, safety and liveness, real-time response, etc. So far modelling and formalizing attempts have been very piecemeal approaches. This paper describes our analysis of a pervasive case study (MATCH, a homecare application) and our proposal for formal (particularly verification) approaches. Our goal is to see to what extent current state of the art formal methods are capable of coping with the verification demand introduced by pervasive systems, and to point out their limitations

A scalable framework for healthcare monitoring application using the Internet of Medical Things

Internet of Things (IoT) is finding application in many areas, particularly in health care where an IoT can be effectively used in the form of an Internet of Medical Things (IoMT) to monitor the patients remotely. The quality of life of the patients and health care outcomes can be improved with the deployment of an IoMT because health care professionals can monitor conditions; access the electronic medical records and communicates with each other. This remote monitoring and consultations might reduce the traditional stressful and costly exercise of frequent hospitalization. Also, the rising costs of health care in many developed countries have influenced the introduction of the Healthcare Monitoring Application (HMA) to their existing health care practices. To materialize the HMA concepts for successful deployment for civilian and commercial use with ease, application developers can benefit from a generic, scalable framework that provides significant components for building an HMA. In this chapter, a generic maintainable HMA is advanced by amalgamating the advantages of event-driven and the layered architecture. The proposed framework is used to establish an HMA with an end-to-end Assistive Care Loop Framework (ACLF) to provide a real-time alarm and assistance to monitor pregnant women. © 2020 John Wiley & Sons, Ltd