Energy Efficient Telemonitoring of Physiological Signals via Compressed Sensing: A Fast Algorithm and Power Consumption Evaluation

@article{Liu2014EnergyET,
  title={Energy Efficient Telemonitoring of Physiological Signals via Compressed Sensing: A Fast Algorithm and Power Consumption Evaluation},
  author={Benyuan Liu and Zhilin Zhang and Gary Xu and Hongqi Fan and Qiang Fu},
  journal={Biomed. Signal Proc. and Control},
  year={2014},
  volume={11},
  pages={80-88}
}
Wireless telemonitoring of physiological signals is an important topic in eHealth. In order to reduce on-chip energy consumption and extend sensor life, recorded signals are usually compressed before transmission. In this paper, we adopt compressed sensing (CS) as a low-power compression framework, and propose a fast block sparse Bayesian learning (BSBL) algorithm to reconstruct original signals. Experiments on real-world fetal ECG signals and epilepsy EEG signals showed that the proposed… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 31 CITATIONS

Compression via compressive sensing: A low-power framework for the telemonitoring of multi-channel physiological signals

  • 2013 IEEE International Conference on Bioinformatics and Biomedicine
  • 2013
VIEW 12 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

The distortion of data compression via compressed sensing in EEG telemonitoring for the epileptic

  • 2016 IEEE Biomedical Circuits and Systems Conference (BioCAS)
  • 2016
VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Weighted mixed-norm minimization based joint compressed sensing recovery of multi-channel electrocardiogram signals

  • Computers & Electrical Engineering
  • 2016
VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Improving EEG Source Localization Through Spatio-Temporal Sparse Bayesian Learning

  • 2018 26th European Signal Processing Conference (EUSIPCO)
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

Tempo-Spatial Compressed Sensing of Organ-on-a-Chip for Pervasive Health

  • IEEE Journal of Biomedical and Health Informatics
  • 2018
VIEW 1 EXCERPT
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 33 REFERENCES

The Effects of Lossy Compression on Diagnostically Relevant Seizure Information in EEG Signals

  • IEEE Journal of Biomedical and Health Informatics
  • 2013
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

An energy efficient compressed sensing framework for the compression of electroencephalogram signals

R. K. Ward S. Fauvel
  • Sensors
  • 2014

Micó - Tormos , Characterization of sample entropy in the context of biomedical signal analysis

D. Cuesta-Frau, D. Austin, P.
  • 2012

Similar Papers

Loading similar papers…