title: Reliability-based rearrangement of ECG automated interpretation chain.
abstract: OBJECTIVE
  Sequences of electrocardiogram (ECG) interpretation procedures from various manufacturers of ECG-dedicated software were studied in aspect of data flow and reliability of intermediate results. The results motivated us to design a new system architecture considering error propagation issues on subsequent stages of ECG processing and reducing the data stream on initial stages.
  
  
  METHODS
  The proposed architecture has network topology and consists of the procedures interconnected by data buses. Each node and isolated sub-networks were tested against the MIT-BIH, CSE standard databases and described by the incorrect result probability and data reduction efficiency. The optimized solution considers also the probability of the procedure use and probability of useless outcome. Best performing network was selected and compared to the original sequential interpretation chain.
  
  
  RESULTS
  The optimized architecture moves reduction-effective functions to the front of the processing chain, reduces the cumulative error propagation by parallel use of multiple short processing chains and reduces the interpretation processing time and the required computational power. Depending on interpretation domain, the reduction of outcome relative inaccuracy was up to 87% (from 2.8% to 1.5%) for pacemaker pulse detection or 70% (from 6.3% to 3.7%) for wave axes determination.
  
  
  CONCLUSIONS
  Significant improvements in automated ECG interpretation were achieved by rearrangement of processing chain only, without any change in processing methods. Reduction of the data stream at early processing stages is particularly advantageous in wireless interpretation system, since task sharing involves minimum exploitation costs.
authors.affiliation: AGH University of Science and Technology, Krakow, Poland. august@agh.edu.pl
authors.forename: Piotr
authors.initials: P
authors.lastname: Augustyniak
mesh_terms: D004562:Electrocardiography; D006801:Humans; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted