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Tytuł artykułu

Interpretive software conversion following changes of patient status and diagnostic goals

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Języki publikacji
EN
Abstrakty
EN
This paper presents selected issues concerning the on-the-run conversion of ECG interpretive software following the changes of the patient status and diagnostic goals. The adaptation of diagnostic procedure, common in human action, but still absent in computerized processing, raises the necessity of including the additional medical knowledge in the feedback loop controlling the diagnostic process. Considering this knowledge in the form of complementary data attributes and the use of modern information processing and digital communication techniques opens up the opportunity to simulate a continuous presence of cardiology expert accompanying the patient in motion. At the same time, the software does not assume the exclusive correctness of the automated diagnosis and provides a human expert with verification tools at all stages of signal processing. The portable remote recorder was designed and prototyped in our laboratory allowing various approaches to automatic software adaptation to be tested.
Rocznik
Strony
3--11
Opis fizyczny
Bibliogr. 19 poz., rys.
Twórcy
Bibliografia
  • [1] CHIARUGI F., TRYPAKIS D., KONTOGIANNIS V., LEES V., CHRONAKI C.E., ZEAKI M., GIANNAKOUDAKIS N., VOURVAHAKIS D., TSIKNAKIS M., Continuous ECG Monitoring in the Management of Pre-Hospital Health Emergencies, Computers in Cardiology, 2003, Vol. 30, 205–208.
  • [2] PINNA G.D., MAESTRI R., GOBBI E., LA ROVERE M.T., SCANFERLATO M.T., Home Telemonitoring of Chronic Heart Failure Patients: Novel System Architecture of the Home or Hospital in Heart Failure Study, Computers in Cardiology, 2003, Vol. 30, 105–108.
  • [3] BANITSAS K.A., GEORGIADIS P., TACHAKRA S., CAVOURAS D., Using handheld devices for real-time wireless teleconsultation, Proc. 26th Annual International Conference of the IEEE EMBS, 2004, 3105–3108.
  • [4] AUGUSTYNIAK P., Request-driven ECG interpretation based on individual data validity periods, Proc. 29th IEEE EMBS Annual International Conference, 2007, 3777–3780.
  • [5] AUGUSTYNIAK P., How a Human Ranks the ECG Diagnostic Parameters: The Pursuit of Experts’ Preferences Based on a Hidden Poll, Computers in Cardiology, 2008, Vol. 35, 449–452.
  • [6] STRASZECKA E., Matching Knowledge and Evidence in a Model of Medical Diagnosis,. Information Technologies in Biomedicine, 2008, 429–436.
  • [7] TADEUSIEWICZ R., AUGUSTYNIAK P., Information Flow and Data Reduction in the ECG Interpretation Process, [in:] Zhang Y.T., Xu L.X., Roux C., Zhuang T.G., Tamura T., Galiana H.L. (eds.), Innovation from Biomolecules to Biosystems, IEEE 27-th Annual IEEE-EMBS Conference, 2005, paper No. 88.
  • [8] MOODY G., MIT/BIH Arrhythmia Database Distribution, Massachusetts Institute of Technology, Division of Health Science and Technology, Cambridge, MA, 1993.
  • [9] WILLEMS J.L., Common Standards for Quantitative Electrocardiography, 10-th CSE Progress Report, ACCO publ. Leuven, 1990.
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  • [13] ECAPS-12C User Guide: Interpretation Standard revision A. Nihon Kohden, 2001.
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  • [15] AUGUSTYNIAK P., TADEUSIEWICZ R., Modeling of ECG Interpretation Methods Sharing Based on Human Experts Relations, Proc. 28th IEEE EMBS Annual International Conference, 2006, 4663–4669.
  • [16] AUGUSTYNIAK P., Content-Adaptive Signal and Data in Pervasive Cardiac Monitoring, Computers in Cardiology, 2005, Vol. 32, 825–828.
  • [17] AUGUSTYNIAK P., Detecting patient’s emergency – a minimum-computation procedure for pervasive cardiac monitoring, Proc. 30th IEEE EMBS Annual International Conference, 2008, 1439–1442.
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  • [19] IEC 60601-2-51. Medical electrical equipment: Particular requirements for the safety, including essential performance, of ambulatory electrocardiographic systems, first edition 2003-02, International Electrotechnical Commission, Geneva, 2003.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPBB-0001-0018
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