Nicole Koenig1, Andrea Seeck2, Jens Eckstein3, Andreas Mainka2, Thomas Huebner2, Andreas Voss1, Stefan Weber4. 1. 1 Ernst-Abbe-Hochschule Jena, University of Applied Sciences , Jena, Germany . 2. 2 Preventicus GmbH in Jena , Jena, Germany . 3. 3 Internal Medicine, University Hospital of Basel , Basel, Switzerland . 4. 4 University Hospital of Regensburg , Regensburg, Germany .
Abstract
INTRODUCTION: This study investigates the accuracy of a heart rate (HR) measurement algorithm applied to a pulse wave. This was based on video signals recorded with a smartphone. The results of electrocardiographic HR and standard linear heart rate variability (HRV) analysis were used for reference. MATERIALS AND METHODS: On a total of 68 subjects, an electrocardiogram (ECG) and the pulse curve were simultaneously recorded on an Apple iPhone 4S. The HR was measured using an algorithm developed by the authors that works according to a method combining the detection of the steepest slope of every pulse wave with the correlation to an optimized pulse wave pattern. RESULTS: The results of the HR measured by pulse curves were extremely consistent (R > 0.99) with the HR measured on ECGs. For most standard linear HRV parameters as well, high correlations of R ≥ 0.90 in the analysis were achieved in the time and frequency domain. CONCLUSION: In conclusion, the overall accuracy of HR and HRV indices of pulse wave analysis, based on video signals of a smartphone, with the developed algorithm was sufficient for preclinical screening applications.
INTRODUCTION: This study investigates the accuracy of a heart rate (HR) measurement algorithm applied to a pulse wave. This was based on video signals recorded with a smartphone. The results of electrocardiographic HR and standard linear heart rate variability (HRV) analysis were used for reference. MATERIALS AND METHODS: On a total of 68 subjects, an electrocardiogram (ECG) and the pulse curve were simultaneously recorded on an Apple iPhone 4S. The HR was measured using an algorithm developed by the authors that works according to a method combining the detection of the steepest slope of every pulse wave with the correlation to an optimized pulse wave pattern. RESULTS: The results of the HR measured by pulse curves were extremely consistent (R > 0.99) with the HR measured on ECGs. For most standard linear HRV parameters as well, high correlations of R ≥ 0.90 in the analysis were achieved in the time and frequency domain. CONCLUSION: In conclusion, the overall accuracy of HR and HRV indices of pulse wave analysis, based on video signals of a smartphone, with the developed algorithm was sufficient for preclinical screening applications.
Entities:
Keywords:
Cardiology; heart rate variability; m-Health; pulse wave analysis; smartphone; video signal
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