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Innovative Solutions in Health Monitoring at Home: The Real-Time Assessment of Serum Potassium Concentration from ECG

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 7251)

Abstract

Maintenance of normal potassium homeostasis is increasingly an important limiting factor in the therapy of several diseases including patients with heart failure. Nowadays, quantification of potassium concentration in the blood ([K + ]) is invasive and laboratory-based. The aims of the study were to develop a method quantifying [K + ] from the electrocardiogram (ECG) and validate it on 13 hemodialysis (HD) and 7 congenital long-QT type 2 (LQT2) patients. Reference values were obtained from blood samples. An ECG-based potassium estimator (KECG) was defined and compared to the reference values. Data from 33/39 HD sessions gave consistent results. In 6 sessions, the presence of a systematic error inhibited reliable estimates. Patient specific calibration allowed good agreement in all HD patients (error: -0.04±0.61mM). As expected, [K + ] was significantly underestimated in LQT2 patients (error: 1.24±0.75mM, p<0.01). Preliminary results show KECG estimates can be an effective tool for hyper/hypokalemic risk patient monitoring at home.

Keywords

  • electrocardiography
  • potassium
  • home health monitoring
  • kidney
  • long-QT syndrome

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© 2012 Springer-Verlag Berlin Heidelberg

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Corsi, C., De Bie, J., Mortara, D., Severi, S. (2012). Innovative Solutions in Health Monitoring at Home: The Real-Time Assessment of Serum Potassium Concentration from ECG. In: Donnelly, M., Paggetti, C., Nugent, C., Mokhtari, M. (eds) Impact Analysis of Solutions for Chronic Disease Prevention and Management. ICOST 2012. Lecture Notes in Computer Science, vol 7251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30779-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-30779-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30778-2

  • Online ISBN: 978-3-642-30779-9

  • eBook Packages: Computer ScienceComputer Science (R0)