An automatic gain control circuit to improve ECG acquisition

1Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

Abstract

Introduction: Long-term electrocardiogram (ECG) recordings are widely employed to assist the diagnosis of cardiac and sleep disorders. However, variability of ECG amplitude during the recordings hampers the detection of QRS complexes by algorithms. This work presents a simple electronic circuit to automatically normalize the ECG amplitude, improving its sampling by analog to digital converters (ADCs). Methods: The proposed circuit consists of an analog divider that normalizes the ECG amplitude using its absolute peak value as reference. The reference value is obtained by means of a full-wave rectifier and a peak voltage detector. The circuit and tasks of its different stages are described. Results: Example of the circuit performance for a bradycardia ECG signal (40bpm) is presented, the signal has its amplitude suddenly halved, and later, restored. The signal is automatically normalized after 5 heart beats for the amplitude drop. For the amplitude increase, the signal is promptly normalized. Conclusion: The proposed circuit adjusts the ECG amplitude to the input voltage range of ADC, avoiding signal to noise ratio degradation of the sampled waveform in order to allow a better performance of processing algorithms.

References Powered by Scopus

Get full text

A duty-cycle controlled variable-gain instrumentation amplifier applied for two-electrode ECG measurement

9Citations
19Readers
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Rovetta, M., Baggio, J. F. R., & Moraes, R. (2017). An automatic gain control circuit to improve ECG acquisition. Research on Biomedical Engineering, 33(4), 370–374. https://doi.org/10.1590/2446-4740.04217

Readers over time

‘19‘20‘21‘23‘2401234

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

67%

Researcher 2

33%

Readers' Discipline

Tooltip

Engineering 5

63%

Materials Science 2

25%

Computer Science 1

13%

Save time finding and organizing research with Mendeley

Sign up for free
0