• DocumentCode
    704099
  • Title

    An ultra-low power dual-mode ECG monitor for healthcare and wellness

  • Author

    Bortolotti, Daniele ; Mangia, Mauro ; Bartolini, Andrea ; Rovatti, Riccardo ; Setti, Gianluca ; Benini, Luca

  • Author_Institution
    DEI, Univ. of Bologna, Bologna, Italy
  • fYear
    2015
  • fDate
    9-13 March 2015
  • Firstpage
    1611
  • Lastpage
    1616
  • Abstract
    Technology scaling enables today the design of ultra-low cost wireless body sensor networks for wearable biomedical monitors. These devices, according to the application domain, show greatly varying tradeoffs in terms of energy consumption, resources utilization and reconstructed biosignal quality. To achieve minimal energy operation and extend battery life, several aspects must be considered, ranging from signal processing to the technological layers of the architecture. The recently proposed Rakeness-based Compressed Sensing (CS) expands the standard CS paradigm deploying the localization of input signal energy to further increase data compression without sensible RSNR degradation. This improvement can be used either to optimize the usage of a non volatile memory (NVM) to store in the device a record of the biosignal or to minimize the energy consumption for the transmission of the entire signal as well as some of its features. We specialize the sensing stage to achieve signal qualities suitable for both Healthcare (HC) and Wellness (WN), according to an external input (e.g. the patient). In this paper we envision a dual-operation wearable ECG monitor, considering a multi-core DSP for input biosignal compression and different technologies for either transmission or local storage. The experimental results show the effectiveness of the Rakeness approach (up to ≈ 70% more energy efficient than the baseline) and evaluate the energy gains considering different use case scenarios.
  • Keywords
    body sensor networks; compressed sensing; data compression; electrocardiography; health care; medical signal processing; random-access storage; RSNR degradation; Rakeness approach; Rakeness-based compressed sensing; biosignal quality; data compression; dual-operation wearable ECG monitor; energy consumption; healthcare; multicore DSP; nonvolatile memory; signal processing; ultralow cost wireless body sensor networks; ultralow power dual-mode ECG monitor; wearable biomedical monitors; Biomedical monitoring; Digital signal processing; Electrocardiography; Medical services; Monitoring; Sensors; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015
  • Conference_Location
    Grenoble
  • Print_ISBN
    978-3-9815-3704-8
  • Type

    conf

  • Filename
    7092651