Development of data acquisition components for simultaneous recording of 3D epicardial and surface ECG signals in the langendorff perfusion apparatus

2016 ◽  
Author(s):  
Ryan Wade Selby ◽  
Anup Jonchhe ◽  
Chen Kaplan ◽  
Coeli M. Lopes ◽  
Behnaz Ghoraani
Keyword(s):  
Data Acquisition ◽  
Simultaneous Recording ◽  
Ecg Signals ◽  
Surface Ecg ◽  
Langendorff Perfusion ◽  
Perfusion Apparatus

scholarly journals A new wearable multichannel magnetocardiogram system with a SERF atomic magnetometer array

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yanfei Yang ◽  
Mingzhu Xu ◽  
Aimin Liang ◽  
Yan Yin ◽  
Xin Ma ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Data Acquisition ◽  
Current Distribution ◽  
Spin Exchange ◽  
Healthy Human ◽  
Ecg Signals ◽  
Mode Decomposition ◽  
Magnetometer Array ◽  
Data Acquisition And Processing ◽  
Electrocardiogram Ecg

AbstractIn this study, a wearable multichannel human magnetocardiogram (MCG) system based on a spin exchange relaxation-free regime (SERF) magnetometer array is developed. The MCG system consists of a magnetically shielded device, a wearable SERF magnetometer array, and a computer for data acquisition and processing. Multichannel MCG signals from a healthy human are successfully recorded simultaneously. Independent component analysis (ICA) and empirical mode decomposition (EMD) are used to denoise MCG data. MCG imaging is realized to visualize the magnetic and current distribution around the heart. The validity of the MCG signals detected by the system is verified by electrocardiogram (ECG) signals obtained at the same position, and similar features and intervals of cardiac signal waveform appear on both MCG and ECG. Experiments show that our wearable MCG system is reliable for detecting MCG signals and can provide cardiac electromagnetic activity imaging.

Effects of heart isolation, voltage-sensitive dye, and electromechanical uncoupling agents on ventricular fibrillation

2003 ◽  
Vol 284 (5) ◽  
pp. H1818-H1826 ◽  
Author(s):  
Hao Qin ◽  
Matthew W. Kay ◽  
Nipon Chattipakorn ◽  
David T. Redden ◽  
Raymond E. Ideker ◽  
...  
Keyword(s):  
Ventricular Fibrillation ◽  
Pattern Analysis ◽  
Electrode Array ◽  
Left Ventricular ◽  
Control Data ◽  
Voltage Sensitive Dye ◽  
Activation Patterns ◽  
Langendorff Perfusion ◽  
Perfusion Apparatus ◽  
Diacetyl Monoxime

We tested whether the interventions typically required for optical mapping affect activation patterns during ventricular fibrillation (VF). A 21 × 24 unipolar electrode array (1.5 mm spacing) was sutured to the left ventricular epicardium of 16 anesthetized pigs, and four episodes of electrically induced VF (30-s duration) were recorded. The hearts were then rapidly excised and connected to a Langendorff perfusion apparatus. Four of the hearts were controls, in which 24 additional VF episodes were then mapped. In the remaining 12 hearts, four VF episodes were mapped after isolation, four more episodes were mapped after exposure to the voltage-sensitive dye di-4-ANEPPS, and six more episodes were mapped after exposure to the electromechanical uncoupling agents diacetyl monoxime (DAM; 20 mmol/l, n = 6) or cytochalasin D (CytoD; 10 μmol/l, n = 6). VF episodes were separated by 4 min. VF activation patterns were quantified using custom pattern analysis algorithms. From comparisons with time-corrected control data, all interventions significantly changed VF patterns. Most changes were broadly consistent with slowing and regularization due to loss of excitability. Heart isolation had the largest effect on VF patterns, followed by CytoD, DAM, and dye.

scholarly journals Improved cardiac protection with Sabax cardioplegia in Langendorff isolated rat hearts

2014 ◽  
Vol 60 (6) ◽  
pp. 254-259
Author(s):  
M. Perian ◽  
M. Mărginean ◽  
D. Dobreanu ◽  
Alina Scridon
Keyword(s):  
Myocardial Protection ◽  
Myocardial Injury ◽  
Left Ventricular ◽  
Mechanical Activity ◽  
Cardioplegic Arrest ◽  
Rat Hearts ◽  
Langendorff Perfusion ◽  
Perfusion Apparatus ◽  
Solution Methods ◽  
Male Wistar Rats

Abstract Objective: Cardioplegia is an important step to facilitate cardiac surgery while limiting intraoperative myocardial injury. Although recent advances in cardioplegic arrest methods have significantly contributed to better postoperative outcomes, there is still controversy regarding the optimal composition and temperature of the cardioplegic solution. Accordingly, we aimed to assess whether cold or lukewarm Sabax cardioplegia offer improved myocardial protection compared with the classical Krebs-Henseleit solution. Methods: The hearts of 40 male Wistar rats were isolated and submitted to constant-flow retrograde perfusion using a Langendorff perfusion apparatus. The hearts were randomly assigned to cold Krebs-Henseleit (K-H), cold Sabax, or lukewarm Sabax cardioplegia. The ECG, heart rates, and left ventricular systolic pressures (LVSP) were recorded pre- and post-cardioplegia. The time needed for cardioplegia induction and post-cardioplegia recovery were also noted. Results: Both cold and lukewarm Sabax cardioplegia insured faster induction and faster recovery following isothermic reperfusion compared to the standard K-H solution (both p< 0.01). With K-H cardioplegia, the hearts presented a 21.7% force loss after reperfusion (p< 0.001), whilst Sabax cardioplegia was associated with a slight increase in ventricular mechanical activity (3% LVSP increase with lukewarm Sabax cardioplegia, p< 0.001 and 2% LVSP increase with cold Sabax cardioplegia, p = 0.02). With Sabax cardioplegia the hearts displayed considerably less major arrhythmic events and presented less significant bradycardia. Conclusions: The present data suggest that Sabax cardioplegia may be superior to the classical cold crystalloid K-H solution in preserving mechanical activity of the heart and may provide superior protection against major arrhythmias.

scholarly journals On the Impact of the Data Acquisition Protocol on ECG Biometric Identification

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4645
Author(s):  
Mariana S. Ramos ◽  
João M. Carvalho ◽  
Armando J. Pinho ◽  
Susana Brás
Keyword(s):  
Data Acquisition ◽  
Signal Wave ◽  
Biometric Identification ◽  
Identification System ◽  
Time Interval ◽  
Essential Information ◽  
Ecg Signals ◽  
Movement Data ◽  
Long Time ◽  
The Impact

Electrocardiographic (ECG) signals have been used for clinical purposes for a long time. Notwithstanding, they may also be used as the input for a biometric identification system. Several studies, as well as some prototypes, are already based on this principle. One of the methods already used for biometric identification relies on a measure of similarity based on the Kolmogorov Complexity, called the Normalized Relative Compression (NRC)—this approach evaluates the similarity between two ECG segments without the need to delineate the signal wave. This methodology is the basis of the present work. We have collected a dataset of ECG signals from twenty participants on two different sessions, making use of three different kits simultaneously—one of them using dry electrodes, placed on their fingers; the other two using wet sensors placed on their wrists and chests. The aim of this work was to study the influence of the ECG protocol collection, regarding the biometric identification system’s performance. Several variables in the data acquisition are not controllable, so some of them will be inspected to understand their influence in the system. Movement, data collection point, time interval between train and test datasets and ECG segment duration are examples of variables that may affect the system, and they are studied in this paper. Through this study, it was concluded that this biometric identification system needs at least 10 s of data to guarantee that the system learns the essential information. It was also observed that “off-the-person” data acquisition led to a better performance over time, when compared to “on-the-person” places.

scholarly journals Microprocessor-based simulator of surface ECG signals

2007 ◽  
Vol 90 ◽  
pp. 012030 ◽  
Author(s):  
A E Martínez ◽  
E Rossi ◽  
L Nicola Siri
Keyword(s):  
Ecg Signals ◽  
Surface Ecg

scholarly journals Data-driven beamforming techniques to attenuate ballistocardiogram (BCG) artefacts in EEG-fMRI without detecting cardiac pulses in electrocardiography (ECG) recordings

2020 ◽  
Author(s):  
Makoto Uji ◽  
Nathan Cross ◽  
Florence B. Pomares ◽  
Aurore A. Perrault ◽  
Aude Jegou ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Data Acquisition ◽  
Spatial Filtering ◽  
Data Driven ◽  
Fmri Data ◽  
Eeg Signals ◽  
Ecg Signals ◽  
Filtering Technique ◽  
Cardiac Pulse ◽  
Beamforming Technique

AbstractSimultaneous recording of EEG and fMRI is a very promising non-invasive neuroimaging technique, providing a wide range of complementary information to characterize underlying mechanisms associated with brain functions. However, EEG data obtained from the simultaneous EEG-fMRI recordings are strongly influenced by MRI related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. The GA is induced by temporally varying magnetic field gradients used for MR imaging, whereas the BCG artefacts are produced by cardiac pulse driven head motion in the strong magnetic field of the MRI scanner, so that this BCG artefact will be present when the subject is lying in the scanner, even when no fMRI data are acquired. When compared to corrections of the GA, the BCG artefact corrections are more challenging to remove due to its inherent variabilities and dynamic changes over time. Typically, the BCG artefacts obscure the EEG signals below 20Hz, and this remains problematic especially when the frequency of interest of EEG signals is below 20Hz, such as Alpha (8-13Hz) and Beta (13-30Hz) band EEG activity, or sleep spindle (11-16Hz) and slow-wave oscillations (<1 Hz) during sleep. The standard BCG artefact corrections, as for instance Average Artefact Subtraction method (AAS), require detecting cardiac pulse (R-peak) events from simultaneous electrocardiography (ECG) recordings. However, ECG signals in the MRI scanner are sometimes distorted and will become problematic for detecting reliable R-peaks. In this study, we focused on a beamforming technique, which is a spatial filtering technique to reject sources of signal variance that do not appear dipolar in the source space. This technique attenuates all unwanted source activities outside of a presumed region of interest without having to specify the location or the configuration of these underlying source signals. Specifically, in this study, we revisited the advantages of the beamforming technique to attenuate the BCG artefact in EEG-fMRI, and also to recover meaningful task-based induced neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond as accurately and quickly as possible. We analysed EEG-fMRI data in 20 healthy participants when they were performing the ANT, and compared four different BCG correction approaches (non-BCG corrected, AAS BCG corrected, beamforming+AAS BCG corrected, beamforming BCG corrected). We demonstrated that beamforming BCG corrected data did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task-based induced brain activity when compared to the standard AAS BCG corrections. Without detecting R-peak events from the ECG, this data-driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG-fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI related artefacts.HighlightsBeamforming spatial filtering technique attenuates ballistocardiogram (BCG) artefacts in EEG-fMRI without detecting cardiac pulses in electrocardiography (ECG) recordings.Beamforming BCG denoising technique recovers expected task-based induced visual alpha and motor beta event-related desynchronization (ERD).Beamforming technique improves signal-noise ratios (SNR) of neural activities as compared to sensor level signals.Data-driven beamforming technique appears promising for longer data acquisition of sleep and resting EEG-fMRI without relying on ECG signals.

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