The in-ear region as a novel anatomical site for ECG signal detection: validation study on healthy volunteers

Abstract

Purpose

Early detection of cardiac arrhythmias is a major opportunity for mobile health, as wearable devices nowadays available can detect single-lead electrocardiogram (ECG). The study aims to validate the in-ear region as a new anatomical site for ECG signal detection and looks towards designing innovative ECG wearable devices.

Methods

We performed ECG using KardiaMobile device (AliveCor®) on 35 healthy volunteers. First, ECG was detected by standard modality using both hands. Then, ECG was detected using the left in-ear region instead of the right hand. All the recorded ECGs were analyzed by the device and by two cardiologists in blind testing.

Results

We successfully collected 70 ECGs performed on 35 volunteers (male 54%, age 39.1 ± 10.7 years; BMI 22.9 ± 2.89 kg/m2) with no differences observed by KardiaMobile in ECG reports detected in the two different modalities. All the ECGs were reported as normal by the device and the two cardiologists. Moreover, linear regression analysis showed good correlation between the amplitude (mV) of P (r = 0.76; r2 = 0.57; p < 0.0001) and QRS waves (r = 0.81; r2 = 0.65; p < 0.0001), the intervals (ms) of PR (r = 0.91; r2 = 0.83; p < 0.0001; LOA − 0.60–0.41; CC = 0.91), QRS (r = 0.78; r2 = 0.61; p < 0.0001; LOA − 0.49–0.43; CC = 0.78), QT (r = 0.85; r2 = 0.71; p < 0.0001; LOA − 1.31–1.20; CC = 0.85), and heart rate (r = 0.94; r2 = 0.89; p < 0.0001; LOA − 7.82–7.76; CC = 0.94) detected in two different modalities.

Conclusion

The in-ear region is a reliable novel anatomical site for ECG signal detection in normal healthy subjects. Further studies are needed to validate this new ECG detection modality also in case of cardiac arrhythmias and to support the development of new wearable devices.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. 1.

    Turakhia MP, Kaiser DW. Transforming the care of atrial fibrillation with mobile health. J Interv Card Electrophysiol. 2016;47:45–50.

    Article  Google Scholar 

  2. 2.

    Chugh SS, Havmoeller R, Narayanan K, Singh D, Rienstra M, Benjamin EJ, et al. Worldwide epidemiology of atrial fibrillation: a global burden of disease 2010 study. Circulation. 2014;129:837–47.

    Article  Google Scholar 

  3. 3.

    Colilla S, Crow A, Petkun W, Singer DE, Simon T, Liu X. Estimates of current and future incidence and prevalence of atrial fibrillation in the U.S. adult population. Am J Cardiol. 2013;112:1142–7.

    Article  Google Scholar 

  4. 4.

    Krijthe BP, Kunst A, Benjamin EJ, Lip GY, Franco OH, Hofman A, et al. Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur Heart J. 2013;34:2746–51.

    Article  Google Scholar 

  5. 5.

    Zoni-Berisso M, Lercari F, Carazza T, Domenicucci S. Epidemiology of atrial fibrillation: European perspective. Clin Epidemiol. 2014;6:213–20.

    Article  Google Scholar 

  6. 6.

    Steinberg JS, Varma N, Cygankiewicz I, Aziz P, Balsam P, Baranchuk A, et al. 2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry. Heart Rhythm. 2017;14(7):e55–96. https://doi.org/10.1016/j.hrthm.2017.03.038.

    Article  PubMed  Google Scholar 

  7. 7.

    Kim MH, Johnston SS, Chu B-C, Dalal MR, Schulman KL. Estimation of total incremental health care costs in patients with atrial fibrillation in the United States. Circ Cardiovasc Qual Out- comes. 2011;4:313–20.

    Article  Google Scholar 

  8. 8.

    Panaccio MP, Cummins G, Wentworth C, Lanes S, Reynolds SL, Reynolds MW, et al. A common data model to assess cardiovascular hospitalization and mortality in atrial fibrillation patients using administrative claims and medical records. Clin Epidemiol. 2015;7:77–90.

    Article  Google Scholar 

  9. 9.

    Turakhia MP, Ullal AJ, Hoang DD, Than CT, Miller JD, Friday KJ, et al. Feasibility of extended ambulatory electrocardio- gram monitoring to identify silent atrial fibrillation in high-risk patients: the screening study for un- diagnosed atrial fibrillation (STUDY-AF). Clin Cardiol. 2015;38:285–92.

    Article  Google Scholar 

  10. 10.

    Freedman B, Camm J, Calkins H, Healey JS, Rosenqvist M, Wang J, et al. Screening for atrial fibrillation: a report of the AF- SCREEN international collaboration. Circulation. 2017;135:1851–67.

    Article  Google Scholar 

  11. 11.

    Ip JE. Wearable devices for cardiac rhythm diagnosis and management. JAMA. 2019;321(4):337–8.

    Article  Google Scholar 

  12. 12.

    von Rosenberg W, Chanwimalueang T, Goverdovsky V, Peters NS, Papavassiliou C, Mandic DP. Hearables: feasibility of recording cardiac rhythms from head and in-ear locations. R Soc Open Sci. 2017;4(11):171214.

    Article  Google Scholar 

  13. 13.

    Zhang Q, Zhou D. Deep arm/ear-ECG image learning for highly wearable biometric human identification. Ann Biomed Eng. 2018;46:122–34.

    Article  Google Scholar 

  14. 14.

    Nantsupawat T, Nugent K, Phrommintikul A. Atrial fibrillation in the elderly. Drugs Aging. 2013;30(8):593–601.

    CAS  Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to R. De Lucia.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

De Lucia, R., Zucchelli, G., Barletta, V. et al. The in-ear region as a novel anatomical site for ECG signal detection: validation study on healthy volunteers. J Interv Card Electrophysiol 60, 93–100 (2021). https://doi.org/10.1007/s10840-020-00709-x

Download citation

Keywords

  • Digital health
  • Mobile health
  • ECG wearable devices
  • Arrhythmias
  • Atrial fibrillation