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. 2023 Nov 9;15(11):e48563.
doi: 10.7759/cureus.48563. eCollection 2023 Nov.

Handy EKG: A Low-Cost Electrocardiograph for Primary Care

Jhiamluka Solano  1 , Alejandro J Calderón  2 , Servio Paguada  2 , Óscar Hernández  2 , Erick Vladimir Reyes Marín  2 , Hana Sandoval  3 , Kellyn Funes  3 , Raúl-José Palma-Mendoza  2
Affiliations

Handy EKG: A Low-Cost Electrocardiograph for Primary Care

Jhiamluka Solano et al. Cureus. .

Abstract

Background Cardiovascular diseases constitute the majority of noncommunicable disease deaths worldwide. In Honduras, cardiovascular diseases represent the fifth cause of death among individuals aged 45 to 49 years, while 20% of emergency room visits are due to cerebrovascular events, heart failure, and acute myocardial infarction. Methodology A low-cost three-lead electrocardiograph (ECG) (Handy EKG) was designed and manufactured for primary care. The device is supported by Bluetooth connectivity and machine learning. Device readings were collected from volunteers and compared to those obtained with a conventional 12-lead ECG. Results The device provided readings of lead one of a TDOU model CMS600G 12-lead ECG to monitor and diagnose bradyarrhythmia and tachyarrhythmias. Overall, 96% (49) of the readings showed a similarity in morphology, amplitude, and duration of waves, segments, and complexes compared to a 12-lead ECG. The device showed potential for application in primary care and intrahospital settings due to its continuous monitoring capabilities, portability, and possible connectivity with mobile devices. Conclusions The results indicate that the designed platform is safe, offers good quality in its operation at all levels, and provides ECG results equivalent to those of a conventional ECG in most cases (considering only one lead).

Keywords: cardiology devices; electrocardiograph; machine learning models; preventive cardiology; primary care.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Device connection diagram.
Figure 2
Figure 2. Final prototype.
Figure 3
Figure 3. Mobile application interface.
Figure 4
Figure 4. Mobile application interface.
Figure 5
Figure 5. Application database diagram.
Figure 6
Figure 6. Handy EKG ECG tracing.
Figure 7
Figure 7. Comparison of the P wave duration between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the P wave duration in seconds.
Figure 8
Figure 8. Comparison of the P wave voltage between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the voltage of the P wave in mV.
Figure 9
Figure 9. Comparison of the PR segment duration between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the PR segment duration in seconds.
Figure 10
Figure 10. Comparison of the QRS complex duration between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the QRS complex duration in seconds.
Figure 11
Figure 11. Comparison of the T wave duration between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the duration of the T wave in seconds.
Figure 12
Figure 12. Comparison of the amplitude of the T wave between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the voltage of the T wave in mV.
Figure 13
Figure 13. Comparison of the average duration of the QT segment between the conventional ECG and the Handy EKG. The X axis demonstrates the comparison between individual volunteers and the Y axis demonstrates the duration of the QT segment in seconds.
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