Digital Twins for Precision Healthcare

Precision healthcare is an emerging concept that will see technology-driven digital transformation of the health service. It enables customised patient outcomes via the development of novel, targeted medical approaches with a focus on intelligent, data-centric smart healthcare models. Currently, precision healthcare is seen as a challenging model to apply due to the complexity of the healthcare ecosystem, which is a multi-level and multifaceted environment with high real-time interactions among disciplines, practitioners, patients and discrete computer systems. Digital Twins (DT) pairs individual physical artefacts with digital models reflecting their status in real-time. Creating a live-model for healthcare services introduces new opportunities for patient care including better risk assessment and evaluation without disturbing daily activities. In this article, to address design and management in this complexity, we examine recent work in Digital Twins (DT) to investigate the goals of precision healthcare at a patient and healthcare system levels. We further discuss the role of DT to achieve precision healthcare, proposed frameworks, the value of active participation and continuous monitoring, and the cyber-security challenges and ethical implications for this emerging paradigm.

[1]  K. Shea,et al.  Delineation of self-care and associated concepts. , 2011, Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing.

[2]  William H. Sanders,et al.  Developing Models for Physical Attacks in Cyber-Physical Systems , 2017, CPS-SPC@CCS.

[3]  T. Greenhalgh,et al.  Evidence based medicine: a movement in crisis? , 2014, BMJ : British Medical Journal.

[4]  R. Holle,et al.  Disease management programmes for patients with coronary heart disease--an empirical study of German programmes. , 2008, Health policy.

[5]  Juan I. Nieto-Hipólito,et al.  Designing a Model of a Digital Ecosystem for Healthcare and Wellness Using the Business Model Canvas , 2016, Journal of Medical Systems.

[6]  M. Shamim Hossain,et al.  m-Therapy: A Multisensor Framework for in-Home Therapy Management: A Social Therapy of Things Perspective , 2018, IEEE Internet of Things Journal.

[7]  Taïcir Loukil,et al.  The use of discrete event simulation in hospital supply chain management , 2014, 2014 International Conference on Advanced Logistics and Transport (ICALT).

[8]  Tim Watson,et al.  Enabling intelligent cities through cyber security of building information and building systems , 2014 .

[9]  Ophir Vermesh,et al.  Toward achieving precision health , 2018, Science Translational Medicine.

[10]  Duc-Hung Le,et al.  Provisioning Software-Defined IoT Cloud Systems , 2014, 2014 International Conference on Future Internet of Things and Cloud.

[11]  Gregory Epiphaniou,et al.  Anonymity networks and the fragile cyber ecosystem , 2016, Netw. Secur..

[12]  S. Cohn.  ‘Trust my doctor, trust my pancreas’: trust as an emergent quality of social practice , 2015, Philosophy, ethics, and humanities in medicine : PEHM.

[13]  R. Busse,et al.  Disease management programs for type 2 diabetes in Germany: a systematic literature review evaluating effectiveness. , 2014, Deutsches Arzteblatt international.

[14]  Sankaran Mahadevan,et al.  Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft (Preprint) , 2012 .

[15]  Vladimir A. Oleshchuk,et al.  Remote Patient Monitoring Within a Future 5G Infrastructure , 2011, Wirel. Pers. Commun..

[16]  Rui Kang,et al.  Risk assessment method for cyber security of cyber physical systems , 2015, 2015 First International Conference on Reliability Systems Engineering (ICRSE).

[17]  Florian Kammüller,et al.  Attack Tree Analysis for Insider Threats on the IoT Using Isabelle , 2016, HCI.

[18]  Basit Qureshi,et al.  Towards a Digital Ecosystem for Predictive Healthcare Analytics , 2014, MEDES.

[19]  Yutao Ma,et al.  CITY PROFILE: USING SMART DATA TO CREATE DIGITAL URBAN SPACES , 2018, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

[20]  Christian Tahon,et al.  Modeling the emergency path handling And Emergency Department Simulation , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[21]  Shiyan Hu,et al.  Introduction to Cyber-Physical System Security: A Cross-Layer Perspective , 2017, IEEE Transactions on Multi-Scale Computing Systems.

[22]  Jeroen van den Hoven,et al.  Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm , 2018, Front. Genet..

[23]  Heikki Laaki,et al.  Prototyping a Digital Twin for Real Time Remote Control Over Mobile Networks: Application of Remote Surgery , 2019, IEEE Access.

[24]  Salim Hariri,et al.  Anomaly behavior analysis for smart grid automation system , 2017, 2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC).

[25]  Amy M. Sitapati,et al.  Virtual Care 2.0—a Vision for the Future of Data-Driven Technology-Enabled Healthcare , 2019, Current Treatment Options in Cardiovascular Medicine.

[26]  Raymond Y. K. Lau,et al.  Smart health: Big data enabled health paradigm within smart cities , 2017, Expert Syst. Appl..

[27]  L. Hood,et al.  P4 medicine: how systems medicine will transform the healthcare sector and society. , 2013, Personalized medicine.

[28]  Edward H. Glaessgen,et al.  The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles , 2012 .

[29]  Trisha Greenhalgh,et al.  Analysing the role of complexity in explaining the fortunes of technology programmes: empirical application of the NASSS framework , 2018, BMC Medicine.

[30]  Yingdong Zhao,et al.  Application of molecular profiling in clinical trials for advanced metastatic cancers. , 2015, Journal of the National Cancer Institute.

[31]  Roland Rosen,et al.  About The Importance of Autonomy and Digital Twins for the Future of Manufacturing , 2015 .

[32]  Edgar R. Weippl,et al.  Advanced social engineering attacks , 2015, J. Inf. Secur. Appl..

[33]  Patty Kostkova,et al.  Grand Challenges in Digital Health , 2015, Front. Public Health.

[34]  Iain G. Johnston,et al.  Toward Precision Healthcare: Context and Mathematical Challenges , 2017, Front. Physiol..

[35]  Carlos Eduardo Pereira,et al.  Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange , 2016 .

[36]  Paolo Pedrazzoli,et al.  VFF: Virtual Factory Framework , 2010, 2010 IEEE International Technology Management Conference (ICE).

[37]  Darren J. Hartl,et al.  Computationally Efficient Analysis of SMA Sensory Particles Embedded in Complex Aerostructures Using a Substructure Approach , 2015 .

[38]  Karl Waedt,et al.  Forensic readiness of smart buildings: Preconditions for subsequent cybersecurity tests , 2016, 2016 IEEE International Smart Cities Conference (ISC2).

[39]  Insup Lee,et al.  Challenges and Research Directions in Medical Cyber–Physical Systems , 2012, Proceedings of the IEEE.

[40]  M. Shamim Hossain,et al.  Semantic Multimedia Fog Computing and IoT Environment: Sustainability Perspective , 2018, IEEE Communications Magazine.

[41]  Gregory Epiphaniou,et al.  Proactive Threat Detection for Connected Cars Using Recursive Bayesian Estimation , 2018, IEEE Sensors Journal.

[42]  Jing Zhang,et al.  5G-Smart Diabetes: Toward Personalized Diabetes Diagnosis with Healthcare Big Data Clouds , 2018, IEEE Communications Magazine.

[43]  A. Lefevre,et al.  Monitoring and evaluating digital health interventions: a practical guide to conducting research and assessment. , 2016 .

[44]  A. Primm,et al.  Beyond misdiagnosis, misunderstanding and mistrust: relevance of the historical perspective in the medical and mental health treatment of people of color. , 2007, Journal of the National Medical Association.

[45]  Jay Lee,et al.  A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems , 2015 .

[46]  Stuart Young,et al.  IoT and smart city services to support independence and wellbeing of older people , 2017, 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM).

[47]  Dharma P. Agrawal,et al.  Fighting against phishing attacks: state of the art and future challenges , 2016, Neural Computing and Applications.

[48]  Jacques Lamothe,et al.  Pervasive Computing Integrated Discrete Event Simulation for a Hospital Digital Twin , 2018, 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA).

[49]  M. Terris.  Evolution of Public Health and Preventive Medicine in the United States. , 1975, American journal of public health.

[50]  Giancarlo Fortino,et al.  Integration of agent-based and Cloud Computing for the smart objects-oriented IoT , 2014, Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[51]  Arquimedes Canedo,et al.  Industrial IoT lifecycle via digital twins , 2016, 2016 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[52]  Florian Skopik,et al.  A problem shared is a problem halved: A survey on the dimensions of collective cyber defense through security information sharing , 2016, Comput. Secur..

[53]  C. Caspersen,et al.  The effectiveness of disease and case management for people with diabetes. A systematic review. , 2002, American journal of preventive medicine.

[54]  Yajun Fang,et al.  A Survey on the Status of Smart Healthcare from the Universal Village Perspective , 2018, 2018 4th International Conference on Universal Village (UV).

[55]  M. Makary,et al.  Medical error—the third leading cause of death in the US , 2016, British Medical Journal.

[56]  Salim Hariri,et al.  Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System , 2017, 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W).

[57]  P Mellodge,et al.  Remotely Monitoring a Patient's Mobility: A Digital Health Application , 2011, IEEE Potentials.

[58]  Nasib Singh Gill,et al.  EMERGING TRENDS AND FUTURE COMPUTING TECHNOLOGIES: A VISION FOR SMART ENVIRONMENT , 2018 .

[59]  Marlien Herselman,et al.  Digital Health Innovation Ecosystems: From Systematic Literature Review to Conceptual Framework , 2016, CENTERIS/ProjMAN/HCist.

[60]  Gregory Epiphaniou,et al.  Federated Blockchain-Based Tracking and Liability Attribution Framework for Employees and Cyber-Physical Objects in a Smart Workplace , 2019, 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3).

[61]  Ashutosh Tiwari,et al.  The security challenges in the IoT enabled cyber-physical systems and opportunities for evolutionary computing & other computational intelligence , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

[62]  D. Berwick,et al.  Eliminating waste in US health care. , 2012, JAMA.

[63]  Kyung Sup Kwak,et al.  Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications , 2010, Journal of Medical Systems.

[64]  L. Robinson,et al.  The Use of Digital Health Technology and Social Media to Support Breast Screening , 2015 .

[65]  Kim-Kwang Raymond Choo,et al.  Cyber-physical systems information gathering: A smart home case study , 2018, Comput. Networks.

[66]  Qaisar Shafi,et al.  Cyber Physical Systems Security: A Brief Survey , 2012, 2012 12th International Conference on Computational Science and Its Applications.

[67]  David Sinreich,et al.  A simple and intuitive simulation tool for analyzing emergency department operations , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[68]  W. E. Cox,et al.  Product Life Cycles as Marketing Models , 1967 .

[69]  Mohsen Guizani,et al.  Blockchain and IoT-Based Cognitive Edge Framework for Sharing Economy Services in a Smart City , 2019, IEEE Access.

[70]  B. Aguado,et al.  Human genomics projects and precision medicine , 2017, Gene Therapy.

[71]  S. Michael Spottswood,et al.  Reengineering Aircraft Structural Life Prediction Using a Digital Twin , 2011 .

[72]  Michael Schluse,et al.  From simulation to experimentable digital twins: Simulation-based development and operation of complex technical systems , 2016, 2016 IEEE International Symposium on Systems Engineering (ISSE).

[73]  Rob Coppinger.  DESIGN THROUGH THE LOOKING GLASS , 2016 .

[74]  Willian D. de Mattos,et al.  M-Health Solutions Using 5G Networks and M2M Communications , 2016, IT Professional.

[75]  Fei Tao,et al.  Digital twin-driven product design, manufacturing and service with big data , 2017, The International Journal of Advanced Manufacturing Technology.

[76]  Vincent Augusto,et al.  A MODELLING AND SIMULATION FRAMEWORK FOR INTELLIGENT CONTROL OF EMERGENCY UNITS IN THE CASE OF MAJOR CRISIS , 2018, 2018 Winter Simulation Conference (WSC).

[77]  Luca Fumagalli,et al.  Flexible Automation and Intelligent Manufacturing , FAIM 2017 , 27-30 June 2017 , Modena , Italy A review of the roles of Digital Twin in CPS-based production systems , 2017 .

[78]  Fei Wang,et al.  A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin , 2019, IEEE Access.

[79]  Howard L McLeod,et al.  Strategies for integrating personalized medicine into healthcare practice. , 2017, Personalized medicine.