Diagnostic accuracy of a smartphone electrocardiograph in dogs: Comparison with standard 6-lead electrocardiography

Vet J. 2016 Oct:216:33-7. doi: 10.1016/j.tvjl.2016.06.013. Epub 2016 Jun 30.


The diagnostic accuracy of a smartphone electrocardiograph (ECG) in evaluating heart rhythm and ECG measurements was evaluated in 166 dogs. A standard 6-lead ECG was acquired for 1 min in each dog. A smartphone ECG tracing was simultaneously recorded using a single-lead bipolar ECG recorder. All ECGs were reviewed by one blinded operator, who judged if tracings were acceptable for interpretation and assigned an electrocardiographic diagnosis. Agreement between smartphone and standard ECG in the interpretation of tracings was evaluated. Sensitivity and specificity for the detection of arrhythmia were calculated for the smartphone ECG. Smartphone ECG tracings were interpretable in 162/166 (97.6%) tracings. A perfect agreement between the smartphone and standard ECG was found in detecting bradycardia, tachycardia, ectopic beats and atrioventricular blocks. A very good agreement was found in detecting sinus rhythm versus non-sinus rhythm (100% sensitivity and 97.9% specificity). The smartphone ECG provided tracings that were adequate for analysis in most dogs, with an accurate assessment of heart rate, rhythm and common arrhythmias. The smartphone ECG represents an additional tool in the diagnosis of arrhythmias in dogs, but is not a substitute for a 6-lead ECG. Arrhythmias identified by the smartphone ECG should be followed up with a standard ECG before making clinical decisions.

Keywords: Canine; Electrocardiography; Smartphone; Validation.

Publication types

  • Comparative Study
  • Multicenter Study

MeSH terms

  • Animals
  • Arrhythmias, Cardiac / diagnosis
  • Arrhythmias, Cardiac / veterinary*
  • Dog Diseases / diagnosis*
  • Dogs / physiology*
  • Electrocardiography / methods
  • Electrocardiography / veterinary*
  • Female
  • Heart Rate*
  • Male
  • Prospective Studies
  • Sensitivity and Specificity
  • Single-Blind Method
  • Smartphone*