Dictionary-based Monitoring of Premature Ventricular Contractions: An Ultra-Low-Cost Point-of-Care Service
  While cardiovascular diseases (CVDs) are prevalent across economic strata,
the economically disadvantaged population is disproportionately affected due to
the high cost of traditional CVD management. Accordingly, developing an
ultra-low-cost alternative, affordable even to groups at the bottom of the
economic pyramid, has emerged as a societal imperative. Against this backdrop,
we propose an inexpensive yet accurate home-based electrocardiogram(ECG)
monitoring service. Specifically, we seek to provide point-of-care monitoring
of premature ventricular contractions (PVCs), high frequency of which could
indicate the onset of potentially fatal arrhythmia. Note that a traditional
telecardiology system acquires the ECG, transmits it to a professional
diagnostic centre without processing, and nearly achieves the diagnostic
accuracy of a bedside setup, albeit at high bandwidth cost. In this context, we
aim at reducing cost without significantly sacrificing reliability. To this
end, we develop a dictionary-based algorithm that detects with high sensitivity
the anomalous beats only which are then transmitted. We further compress those
transmitted beats using class-specific dictionaries subject to suitable
reconstruction/diagnostic fidelity. Such a scheme would not only reduce the
overall bandwidth requirement, but also localising anomalous beats, thereby
reducing physicians' burden. Finally, using Monte Carlo cross validation on
MIT/BIH arrhythmia database, we evaluate the performance of the proposed
system. In particular, with a sensitivity target of at most one undetected PVC
in one hundred beats, and a percentage root mean squared difference less than
9% (a clinically acceptable level of fidelity), we achieved about 99.15%
reduction in bandwidth cost, equivalent to 118-fold savings over traditional
telecardiology.
