Barcos JC, Humphreys JD, Tello Santacruz IA, Guzman JP, Fernández Recalde ML, Avaca HA, Cáceres Monié CR. Enhancing electrocardiographic analysis by combining a high-resolution 12-lead ECG with novel software tools.
J Electrocardiol 2021;
70:70-74. [PMID:
34929607 DOI:
10.1016/j.jelectrocard.2021.12.001]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 11/24/2021] [Accepted: 12/03/2021] [Indexed: 11/28/2022]
Abstract
INTRODUCTION
Signal-averaged electrocardiography is a non-invasive, computerized technique that amplifies, filters, and averages cardiac electrical signals reducing contaminating noise to obtain a high-resolution record. The most widely used signal averaging (SA) method involves a bipolar X, Y, and Z orthogonal lead system. Information is limited regarding its application in the standard resting 12-lead ECG. A novel system combining a high-resolution 12-lead ECG (HR-ECG) registered by SA with advanced analysis tools is presented.
HISTORY
Original programming of a commercially available signal-averaged HR-ECG device was modified, introducing more exhaustive electrocardiographic assessment instruments.
DESCRIPTION
Using SA techniques and placing surface electrodes in the standard 12-lead ECG positions, a HR-ECG is acquired within a bandwidth of 0.25 to 262 Hz at a rate of 1000 samples per second. It is advisable to average at least 200 cycles, taking three to five minutes to record. The package includes different optional high-frequency filters, manual calipers, zoom/superimposing/amplification functions.
CLINICAL ROLE
The main strength lies in obtaining a low noise HR-ECG with zooming capabilities without definition loss. Other potential advantages are the greater ease in performing high precision analysis and comparing different ECG leads simultaneously.
CURRENT PROBLEMS
The primary limitation is the inability to document intermittent or dynamic electrocardiographic disorders because of averaging similar electrical cardiac cycles.
FUTURE DEVELOPMENTS
Adding artificial intelligence and further refinements in the averaging process could lead to software upgrades.
CONCLUSION
Integrating HR-ECG, obtained through SA techniques, with novel advanced analysis tools can enhance the ability to detect electrocardiographic disorders of permanent expression expeditiously.
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