Noninvasive blood potassium measurement using signal-processed, single-lead ecg acquired from a handheld smartphone

Omar Z Yasin; Zachi Attia; John J Dillon; Christopher V DeSimone; Yehu Sapir; Jennifer Dugan; Virend K Somers; Michael J Ackerman; Samuel J Asirvatham; Christopher G Scott; Kevin E Bennet; Dorothy J Ladewig; Dan Sadot; Amir B Geva; Paul A Friedman

doi:10.1016/j.jelectrocard.2017.06.008

Noninvasive blood potassium measurement using signal-processed, single-lead ecg acquired from a handheld smartphone

J Electrocardiol. 2017 Sep-Oct;50(5):620-625. doi: 10.1016/j.jelectrocard.2017.06.008. Epub 2017 Jun 8.

Authors

Affiliations

¹ Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, USA; Department of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN, USA.
² Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, USA; Department of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN, USA; Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer Sheva, Israel.
³ Nephrology and Hypertension, Mayo Clinic, 200 First Street SW, Rochester, MN, USA.
⁴ Department of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN, USA.
⁵ Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer Sheva, Israel.
⁶ Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester, MN, USA.
⁷ Division of Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, USA.
⁸ Mayo Clinic Ventures, 200 First Street SW, Rochester, MN, USA.
⁹ Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, USA; Department of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN, USA. Electronic address: [email protected].

Abstract

Objective: We have previously used a 12-lead, signal-processed ECG to calculate blood potassium levels. We now assess the feasibility of doing so with a smartphone-enabled single lead, to permit remote monitoring.

Patients and methods: Twenty-one hemodialysis patients held a smartphone equipped with inexpensive FDA-approved electrodes for three 2min intervals during hemodialysis. Individualized potassium estimation models were generated for each patient. ECG-calculated potassium values were compared to blood potassium results at subsequent visits to evaluate the accuracy of the potassium estimation models.

Results: The mean absolute error between the estimated potassium and blood potassium 0.38±0.32 mEq/L (9% of average potassium level) decreasing to 0.6 mEq/L using predictors of poor signal.

Conclusions: A single-lead ECG acquired using electrodes attached to a smartphone device can be processed to calculate the serum potassium with an error of 9% in patients undergoing hemodialysis.

Summary: A single-lead ECG acquired using electrodes attached to a smartphone can be processed to calculate the serum potassium in patients undergoing hemodialysis remotely.

Keywords: Electrocardiogram; End-Stage Renal Disease; Hemodialysis; Hyperkalemia; Potassium.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Electrocardiography / methods*
Female
Humans
Hyperkalemia / diagnosis*
Kidney Failure, Chronic / blood*
Kidney Failure, Chronic / therapy
Male
Middle Aged
Potassium / blood*
Renal Dialysis
Signal Processing, Computer-Assisted
Smartphone*

Substances

Potassium

Grants and funding

R21 EB017649/EB/NIBIB NIH HHS/United States