Performance assessment of dry electrodes for wearable long term cardiac rhythm monitoring: Skin-electrode impedance spectroscopy

Bosnjak, Antonio; Kennedy, Alan; Linares, Pedro; Borges, Maira; McLaughlin, James; Escalona, OJ

doi:10.1109/embc.2017.8037209

Cited by 12 publications

(10 citation statements)

References 8 publications

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“…ECG acquisition systems rely on the stability of the skin-electrode interface impedance for proper operation. In a previous study, Bosnjak et al [22] experimentally characterized this parameter with various dry-electrode materials for wearable cardiac rhythm monitoring systems. Silver-silver chloride (Ag-AgCl) dry electrodes showed the second-best results in the frequency range from 0.05 to 150 Hz.…”

Section: Dry Ecg Electrode Systemmentioning

confidence: 99%

Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias

2019

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This article presents the devising, development, prototyping and assessment of a wearable arm-ECG sensor system (WAMECG1) for long-term non-invasive heart rhythm monitoring, and functionalities for acquiring, storing, visualizing and transmitting high-quality far-field electrocardiographic signals. The system integrates the main building blocks present in a typical ECG monitoring device such as the skin surface electrodes, front-end amplifiers, analog and digital signal conditioning filters, flash memory and wireless communication capability. These are integrated into a comfortable, easy to wear, and ergonomically designed arm-band ECG sensor system which can acquire a bipolar ECG signal from the upper arm of the user over a period of 72 h. The small-amplitude bipolar arm-ECG signal is sensed by a reusable, long-lasting, Ag–AgCl based dry electrode pair, then digitized using a programmable sampling rate in the range of 125 to 500 Hz and transmitted via Wi-Fi. The prototype comparative performance assessment results showed a cross-correlation value of 99.7% and an error of less than 0.75% when compared to a reference high-resolution medical-grade ECG system. Also, the quality of the recorded far-field bipolar arm-ECG signal was validated in a pilot trial with volunteer subjects from within the research team, by wearing the prototype device while: (a) resting in a chair; and (b) doing minor physical activities. The R-peak detection average sensibilities were 99.66% and 94.64%, while the positive predictive values achieved 99.1% and 92.68%, respectively. Without using any additional algorithm for signal enhancement, the average signal-to-noise ratio (SNR) values were 21.71 and 18.25 for physical activity conditions (a) and (b) respectively. Therefore, the performance assessment results suggest that the wearable arm-band prototype device is a suitable, self-contained, unobtrusive platform for comfortable cardiac electrical activity and heart rhythm logging and monitoring.

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Section: Dry Ecg Electrode Systemmentioning

confidence: 99%

Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias

2019

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“…However, the ability to recover a useable signal, that is, a heart generated electrogram signal with tolerable noise content, will depend on three major factors in the electrocardiographic (ECG) recording process. Firstly, stable body-surface electrode performance, with regard to the skin-electrode interface-related noise generation and impedance characteristics [10]. Secondly, a high quality, low noise front-end amplifier and data acquisition system, with sufficient sensitivity so as to resolve the small signals involved [11].…”

Section: Electrode System and Dispositionmentioning

confidence: 99%

“…To gather a clinical database of left-arm ECGs under ethical approval, a sensor system with known high performance on the skin-electrode interface impedance (better than available dry-electrodes) [10] and good potential stability (low noise generation), the BIS-Quatro TM (four-electrode) sensor (Covidien, Mansfield, MA, USA), as used for the BIS TM brain monitoring system (Electroencephalogram signals), was selected for the purpose of this study on the proposed arm-ECG signal denoising algorithm. The selected BIS-Quatro TM sensor system provides four pre-gelled independent sensors along an adhesive band 18 cm long (see Figure 1).…”

Section: Electrode System and Dispositionmentioning

confidence: 99%

Data-Driven ECG Denoising Techniques for Characterising Bipolar Lead Sets along the Left Arm in Wearable Long-Term Heart Rhythm Monitoring

et al. 2017

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Abnormal heart rhythms (arrhythmias) are a major cause of cardiovascular disease and death in Europe. Sudden cardiac death accounts for 50% of cardiac mortality in developed countries; ventricular tachycardia or ventricular fibrillation is the most common underlying arrhythmia. In the ambulatory population, atrial fibrillation is the most common arrhythmia and is associated with an increased risk of stroke and heart failure, particularly in an aging population. Early detection of arrhythmias allows appropriate intervention, reducing disability and death. However, in the early stages of disease arrhythmias may be transient, lasting only a few seconds, and are thus difficult to detect. This work addresses the problem of extracting the far-field heart electrogram signal from noise components, as recorded in bipolar leads along the left arm, using a data driven ECG (electrocardiogram) denoising algorithm based on ensemble empirical mode decomposition (EEMD) methods to enable continuous non-invasive monitoring of heart rhythm for long periods of time using a wrist or arm wearable device with advanced biopotential sensors. Performance assessment against a control denoising method of signal averaging (SA) was implemented in a pilot study with 34 clinical cases. EEMD was found to be a reliable, low latency, data-driven denoising technique with respect to the control SA method, achieving signal-to-noise ratio (SNR) enhancement to a standard closer to the SA control method, particularly on the upper arm-ECG bipolar leads. Furthermore, the SNR performance of the EEMD was improved when assisted with an FFT (fast Fourier transform ) thresholding algorithm (EEMD-fft).

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“…The "3-electrode" technique used by us to characterize the skin-electrode impedance (Z SE ) in [7] is repeated here. In this scheme, two Ag/AgCl electrodes (Ambu, Blue Sensor SP-00-S) are placed in the forearm so that they act as reference and current return.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, we used a set up for the measurements identical to the structured for our previous work [7]. That is, we determined the electrical impedance by means of a Schlumberger SI 1260 impedance/gain-phase analyzer combined with a biological sample interface SOLARTRON 1294 (Solartron 1260 and Solartron 1294, Solartron Analytical, Farnborough, UK).…”

Section: Methodsmentioning

confidence: 99%

Characterizing Dry Electrodes Impedance by Parametric Modeling for Arm Wearable Long-term Cardiac Rhythm Monitoring

Bosnjak

Linares

McLaughlin³

et al. 2017

Computing in Cardiology Conference (CinC)

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Performance assessment of dry electrodes for wearable long term cardiac rhythm monitoring: Skin-electrode impedance spectroscopy

Cited by 12 publications

References 8 publications

Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias

Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias

Data-Driven ECG Denoising Techniques for Characterising Bipolar Lead Sets along the Left Arm in Wearable Long-Term Heart Rhythm Monitoring

Characterizing Dry Electrodes Impedance by Parametric Modeling for Arm Wearable Long-term Cardiac Rhythm Monitoring

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