Signal quality and data fusion for false alarm reduction in the intensive care unit.

@article{Li2012SignalQA,
  title={Signal quality and data fusion for false alarm reduction in the intensive care unit.},
  author={Qiao Li and Gari D. Clifford},
  journal={Journal of electrocardiology},
  year={2012},
  volume={45 6},
  pages={596-603}
}
Due to a lack of integration between different sensors, false alarms (FA) in the intensive care unit (ICU) are frequent and can lead to reduced standard of care. We present a novel framework for FA reduction using a machine learning approach to combine up to 114 signal quality and physiological features extracted from the electrocardiogram, photoplethysmograph, and optionally the arterial blood pressure waveform. A machine learning algorithm was trained and evaluated on a database of 4107… CONTINUE READING

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False arrhythmia alarm suppression using ECG, ABP, and photoplethysmogram (MS thesis)

  • AV Deshmane
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