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      An automatic gain control circuit to improve ECG acquisition

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          Abstract

          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.

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          Revisiting QRS Detection Methodologies for Portable, Wearable, Battery-Operated, and Wireless ECG Systems

          Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.
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            New devices for very long-term ECG monitoring.

            Present day 24-h Holter monitors have been shown to miss many arrhythmias that may occur infrequently or under specific circumstances. The advancement in electronic and adhesive technologies have enabled the development of first generation wearable long-term 14-day patch ECG monitors that attach directly to the skin and require no electrodes and wires to operate. This new technology is unobtrusive to the patients and offers them unprecedented mobility. It enables very long-term monitoring of critical patients while they are carrying out daily activities. The monitors are waterproof, offer good adhesion to the skin and can operate as either recorders or wireless streaming devices.
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              Discrete-Time Signal Processing

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                reng
                Research on Biomedical Engineering
                Res. Biomed. Eng.
                Sociedade Brasileira de Engenharia Biomédica (Rio de Janeiro, RJ, Brazil )
                2446-4732
                2446-4740
                November 2017
                : 33
                : 4
                : 370-374
                Affiliations
                [01] Brescia orgnameIndependent scholar Italy
                [02] Brescia orgname2BiTS Italy
                [03] Florianópolis Santa Catarina orgnameUniversidade Federal de Santa Catarina orgdiv1Electrical and Electronic Engineering Department Brazil
                Article
                S2446-47402017000400370
                10.1590/2446-4740.04217
                55f10b8f-f587-4154-8986-8f6a9fee6535

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 24 July 2017
                : 29 October 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 8, Pages: 5
                Product

                SciELO Brazil


                Biopotential amplifier,QRS detection,Amplitude normalization,AGC,SNR

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