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Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy.

In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsify...

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Published in:Journal of Medical Systems Vol. 40; no. 7; pp. 1 - 10
Main Authors: Wang, Yishan, Doleschel, Sammy, Wunderlich, Ralf, Heinen, Stefan
Format: equations & formulas pictorial research tables/charts tracings Journal Article
Published: Springer Nature Jul2016
Online Access:View this record in EBSCOhost
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        01485598
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      jtl: Journal of Medical Systems
      issn: 01485598
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    pubinfo:
      dt: Jul2016
      vid: 40
      iid: 7
      pid: 237
      pub: Springer Nature
      place: New York, New York
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        115925368
        115925368
        115925368
        10.1007/s10916-016-0526-1
        115925368
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        atl: Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy.
      aug:
        au:
          Wang, Yishan
          Doleschel, Sammy
          Wunderlich, Ralf
          Heinen, Stefan
        affil: Chair of Integrated Analog Circuits and RF Systems, RWTH Aachen University, D-52062 Aachen Germany
      sug:
        subj:
          Digital Compression Evaluation
          Wearable Sensors
          Electrocardiography Equipment and Supplies
          Wireless Communications Equipment and Supplies
          Systems Development
          Systems Implementation
          Algorithms
          Systems Design
          Mobile Applications
          Smartphone
          Home Care Equipment and Supplies
          QRS Complex
      ab: In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsifying basis, various compression ratio (CR) and several reconstruction algorithms are simulated and discussed. Finally the reconstruction is done by the android application (App) on smartphone to display the signal in real time. The power efficiency is measured and compared with the system without CS. The optimum satisfying basis built by 3-level decomposed db4 wavelet coefficients, 1-bit Bernoulli random matrix and the most suitable reconstruction algorithm are selected by the simulations and applied on the sensor node and App. The signal is successfully reconstructed and displayed on the App of smartphone. Battery life of sensor node is extended from 55 h to 67 h. The presented wireless ECG system with CS can significantly extend the battery life by 22 %. With the compact characteristic and long term working time, the system provides a feasible solution for the long term homecare utilization.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        tracings
        Journal Article
      ougenre: Article
    language: English
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