Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers’ heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.

      Related collections

      Most cited references 106

      • Record: found
      • Abstract: found
      • Article: not found

      Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis.

      Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.
        Bookmark
        • Record: found
        • Abstract: not found
        • Article: not found

        A survey of mobile cloud computing: architecture, applications, and approaches

          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          Does sports activity enhance the risk of sudden death in adolescents and young adults?

          We sought to assess the risk of sudden death (SD) in both male and female athletes age 12 to 35 years. Little is known about the risk of SD in adolescents and young adults engaged in sports. We did a 21-year prospective cohort study of all young people of the Veneto Region of Italy. From 1979 to 1999, the total population of adolescents and young adults averaged 1,386,600 (692,100 males and 694,500 females), of which 112,790 (90,690 males and 22,100 females) were competitive athletes. An analysis by gender of risk of SD and underlying pathologic substrates was performed in the athletic and non-athletic populations. There were 300 cases of SD, producing an overall cohort incidence rate of 1 in 100,000 persons per year. Fifty-five SDs occurred among athletes (2.3 in 100,000 per year) and 245 among non-athletes (0.9 in 100,000 per year), with an estimated relative risk (RR) of 2.5 (95% confidence interval [CI] 1.8 to 3.4; p < 0.0001). The RR of SD among athletes versus non-athletes was 1.95 (CI 1.3 to 2.6; p = 0.0001) for males and 2.00 (CI 0.6 to 4.9; p = 0.15) for females. The higher risk of SD in athletes was strongly related to underlying cardiovascular diseases such as congenital coronary artery anomaly (RR 79, CI 10 to 3,564; p < 0.0001), arrhythmogenic right ventricular cardiomyopathy (RR 5.4, CI 2.5 to 11.2; p < 0.0001), and premature coronary artery disease (RR 2.6, CI 1.2 to 5.1; p = 0.008). Sports activity in adolescents and young adults was associated with an increased risk of SD, both in males and females. Sports, per se, was not a cause of the enhanced mortality, but it triggered SD in those athletes who were affected by cardiovascular conditions predisposing to life-threatening ventricular arrhythmias during physical exercise.
            Bookmark

            Author and article information

            Affiliations
            [1 ]Department of Computer Science Technology and Computation, University of Alicante, 03690 Alicante, Spain; david.gil@ 123456ua.es (D.G.); jazorin@ 123456dtic.ua.es (J.A.)
            [2 ]Department of Software and Computing Systems, University of Alicante, 03690 Alicante, Spain; rafamt@ 123456dlsi.ua.es
            [3 ]Department of Computer Systems Architecture, Gdansk University of Technology, 80-233 Gdansk, Poland; julian.szymanski@ 123456eti.pg.gda.pl
            Author notes
            [* ]Correspondence: hmora@ 123456ua.es ; Tel.: +34-96590-3400
            Journal
            Sensors (Basel)
            Sensors (Basel)
            sensors
            Sensors (Basel, Switzerland)
            MDPI
            1424-8220
            10 October 2017
            October 2017
            : 17
            : 10
            28994743
            5676602
            10.3390/s17102302
            sensors-17-02302
            © 2017 by the authors.

            Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

            Categories
            Article

            Comments

            Comment on this article