The use of the digital twin has been quickly adopted in industry in recent years and continues to gain momentum. The recent redefinition of the digital twin from the digital replica of a physical asset to the replica of a living or nonliving entity has increased its potential. The digital twin not only disrupts industrial processes, but also expands the domain of health and well-being towards fostering smart healthcare services in smart cities. In this paper, we propose an ISO/IEEE 11073 standardized digital twin framework architecture for health and well-being. This framework encompasses the process of data collection from personal health devices, the analysis of this data, and conveying the feedback to the user in a loop cycle. The framework proposes a solution to include not only X73 compliant devices, but also noncompliant health devices, by interfacing them with an X73 wrapper module as we explain in this paper. Besides, we propose a configurable X73 mobile application, designed to work with any X73 compliant device. We designed and implemented the proposed framework, and the X73 mobile app, and conducted an experiment as a proof of concept of the digital twin in the domain of health and well-being in smart cities. The experiment shows promising results and the potential of benefiting from the proposed framework, by gaining insights on the health and well-being of individuals, and providing feedback to the individual and caregiver.
Executive function and motor control deficits adversely affect gait performance with age, but the neural correlates underlying this interaction during stair climbing remains unclear. Twenty older adults (72.7 ± 6.9 years) completed single tasks: standing and responding to a response time task (SC), ascending or descending stairs (SMup, SMdown); and a dual-task: responding while ascending or descending stairs (DTup, DTdown). Prefrontal hemodynamic response changes (∆HbO2, ∆HbR) were examined using functional near-infrared spectroscopy (fNIRS), gait speed was measured using in-shoe smart insoles, and vocal response time and accuracy were recorded. Findings revealed increased ∆HbO2 (p = 0.020) and slower response times (p < 0.001) during dual- versus single tasks. ∆HbR (p = 0.549), accuracy (p = 0.135) and gait speed (p = 0.475) were not significantly different between tasks or stair climbing conditions. ∆HbO2 and response time findings suggest that executive processes are less efficient during dual-tasks. These findings, in addition to gait speed and accuracy maintenance, may provide insights into the neural changes that precede performance declines. To capture the subtle differences between stair ascent and descent and extend our understanding of the neural correlates of stair climbing in older adults, future studies should examine more difficult cognitive tasks.
Since the introduction of the ISO/IEEE 11073 personal health device (X73-PHD) standards, as part of ISO/IEEE 11073 family of standards, it has been applied to many health systems developed for personal use. In this systematic literature review, we review existing literature collected using three databases: Scopus, Pub Med, and Web of Science. We propose a classification for personal health systems based on the location in which they are used, the technology used to develop them, and the purpose which is determined by the targeted users. We found 51% of the devices used in such systems are standardized while approximately 40% are not and five systems did not specify the device status (9%). Various adaption techniques were used for standardization. Besides, the pulse oximeter is the most used device in such systems since it was used in 43% of them. In addition, we present the role of the X73-PHD standards in the Internet of Things (IoT) and tele-healthcare systems, discuss the challenges of utilizing this set of standards in health monitoring systems and converting the non-standardized devices into standardized ones. Finally, we propose the requirements of personal health systems based on our review of the literature.
INDEX TERMSCompliant system, ISO/IEEE 11073 personal health device, standard, X73-PHD, health systems requirements, IoT.
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