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ECG performance in simultaneous recordings of five wearable devices using a new morphological noise-to-signal index and Smith-Waterman-based RR interval comparisons.

Dominic BläsingAnja BuderJulian Elias ReiserMaria NisserSteffen DerlienMarcus Vollmer
Published in: PloS one (2022)
Data quality was assessed by two new approaches: analyzing the noise-to-signal ratio using morphSQ, and RR interval quality using Smith-Waterman. Both methods deliver comparable results. However the Smith-Waterman approach allows the direct comparison of RR intervals without the need for signal synchronization whereas morphSQ can be computed locally.
Keyphrases
  • air pollution
  • heart rate
  • quality improvement
  • heart rate variability
  • big data
  • machine learning
  • magnetic resonance imaging
  • computed tomography
  • artificial intelligence
  • deep learning