Electrocardiographic Artifact Research Articles

A BIZZARE ECG

Abstract Electrocardiographic artifacts are common and may interfere with interpretation. We describe a clinical case where a limb lead electrode was placed near the pulsation of the radial artery, which created an artery pulse tapping artifact also called Aslanger‘s sign or electromechanical association. This is a very unique physiological type of electrocardiogram (ECG) artifact generated by the movement of the electrode placed near the pulsatile artery, particularly in hyperdynamic state such as hyperthyroidism, severe anemia, liver cirrhosis and arteriovenous fistula, including dialysis fistula of end–stage renal disease. These kind of artifacts may imitate primary repolarization changes characteristic for acute coronary syndrome, arrhythmias or electrolyte abnormalities; thus, they have the potential to trigger unnecessary tests. Careful inspection of the ECG in Fig.1 revealed that the coupling interval of the QRS complex and the artifact is identical, which signifies that the artifact is synchronous with cardiac cycle. In the given ECG, bizarre changes were seen in all limb leads except lead III, suggesting that the artifact arose from right arm limb electrode. The repeat ECG in Fig.2 was taken such that the electrode was not directly on the pulse, showed disappearance of the artifact. When ecountering unexpected electrocardiographic findings, inspection of the ECG and lead placement may identify the cause. Recognizing such intimidating ECG artifacts is very important to avoid unnecessary interventions in a benign condition.

Occipital Localization of Electrocardiographic Artifacts in Pediatric Electroencephalograms: A Novel Observation and Implications.

Occipital Localization of Electrocardiographic Artifacts in Pediatric Electroencephalograms: A Novel Observation and Implications.

Pseudo-ventricular tachycardia—Diagnostic enigma in the emergency department: A case report

Ventricular tachycardia (VT) is a type of broad complex tachycardia originating from a focus in the ventricle. It is one of the four important rhythms which can lead to cardiac arrest. Accurate and timely diagnosis of true VT is the cornerstone for proper management in the emergency department (ED). We present an interesting case of an electrocardiographic artifact mimicking VT, which led to a diagnostic dilemma in the ED.

Transient P′ waves in a hyperkalemic cat: artifact or dissociation?

A 15-year-old Sphynx cat was referred for cervical ventroflexion, ataxia, and lethargy associated with hypokalemia. After administration of supplemental potassium, the cat became severely hyperkalemic. Transient P′ (vs. pseudo P′ waves) were detected on the electrocardiogram. Over the course of hospitalization, the cat's potassium normalized, and the abnormal P′ waves did not recur. These images are presented to highlight the differential diagnoses for this type of electrocardiogram. Diagnostic considerations included complete or transient atrial dissociation (as a rare consequence of hyperkalemia), atrial parasystole, and various electrocardiographic artifacts. Definitive diagnosis of atrial dissociation requires an electrophysiologic study or echocardiographic documentation of two independent atrial rhythms with associated mechanical activity, but these were unavailable in this case.

A new approach for ECG artifact detection using fine-KNN classification and wavelet scattering features in vital health applications

In this paper, as a new application of machine learning, a K- Nearest Neighbor (KNN) classification model is proposed to recognize artifacts in Electrocardiography (ECG) signal using 3-axis accelerometer signals. A fine KNN model using wavelet scattering coefficients as features of 3-axis accelerometer sensor captured training dataset have been proposed as alternative to other machine learning methods to classify artifacts. In wearable health-monitoring devices, artifact noise results signal deformations and it is not possible to employ filtering methods all the time due to data loss. As a result, wearable ECG monitoring devices are not reliable for critical medical usages. Our proposed model classifies accelerometer sensor samples with high probability of having artifact noises in ECG signal with positive predictive value of 94.7%. High accuracy rate of the proposed model in this work gives it an opportunity to be employed in ECG monitoring wearable devices to capture patients ECG history and labeling artifact samples for noise filtration or signal reconstruction systems to cancel the noise without having signal deformations.

A comparison of methods to suppress electrocardiographic artifacts in local field potential recordings

ObjectiveLocal field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are often contaminated with electrocardiographic (ECG) artifacts that hinder the detection of disease-specific electrical brain activity. MethodsThree ECG suppression methods were evaluated: (1) QRS interpolation of the Perceive toolbox, (2) template subtraction, and (3) singular value decomposition (SVD). LFPs were recorded with the Medtronic PerceptTM PC system in nine Parkinson’s disease patients with stimulation OFF (“OFF-DBS”; anode disconnected) and ON at 0 mA (“ON-DBS 0 mA”; anode connected). Findings were verified with simulated ECG-contaminated time series. ResultsECG artifacts were present in 10 out of 18 ON-DBS 0 mA recordings. All ECG suppression methods drastically reduced artifact-induced beta band (13–35 Hz) power and at least partly recovered the beta peak and beta burst dynamics. Using external ECG recordings and lengthening artifact epoch length improved the performance of the suppression methods. Increasing epoch length, however, elevated the risk of flattening the beta peak and losing beta burst dynamics. ConclusionsThe SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings are adequately chosen. SignificanceECG suppression methods enable analysis of disease-specific neural activity from signals affected by ECG artifacts.

Intraoperative electrocardiograph artifact mimicking ventricular tachycardia during a spine surgery

Ventricular Tachycardia (VT) is a dangerous form of arrhythmia that often warrants immediate treatment. We report here a case of intraoperative VT as a result of Electrocardiograph (EKG) artifacts during a spine surgery.

Importance of ECG in the Diagnosis of Acute Pericarditis and Myocardial Infarction: A Review Article.

A promising scientific field is health monitoring and associated technology. A standard testing method to evaluate and identify heart issues is the electrocardiogram (E.C.G.) and diagnose cardiovascular diseases (CVDs). E.C.G. monitoring technologies are becoming more and more prevalent in publications at an exponential rate. E.C.G.is the most crucial tool for screening cardiology and other medical specialities. Twelve leads can be recorded by traditional E.C.G. equipment, while current E.C.G. systems allow for extra leads also with fewer electrodes. Furthermore, "smart" gadgets allow patients to take an E.C.G. at residence. Presenting different ischemia-related symptoms on the E.C.G. by the most recent recommendations. Presentation of contemporary E.C.G. systems and their possible benefit in identifying ischemia-related E.C.G. symptoms based on recent study findings. The identification of ischemia E.C.G. abnormalities can be facilitated and optimised by current E.C.G. systems using vector-based electrocardiography. Although they can be effective for documenting transient E.C.G. abnormalities, especially inside the S.T. segment, smart non-vector-based devices for patients are primarily beneficial for the diagnosis of arrhythmias and cannot substitute the 12-lead E.C.G. for the diagnosis of ischemia. The electrocardiogram (E.C.G.) is inexpensive and easily accessible, but because of its alleged limited specificity, its utility as a screening tool for early detection of athletes with a cardiac condition in danger of immediate cardiac death is contentious. The interpreting parameters have been continuously evolving over the past 10 years as various efforts have been made to better the separation between healthy and pathological E.C.G. abnormalities in athletes. Electrocardiographic abnormalities that are unrelated to cardiac electrical activity are known as electrocardiographic artefacts. E.C.G.elements, including the baseline and waves, can become altered as a result of artefacts.

Sources of Variation in the Spectral Slope of the Sleep EEG.

The 1/f spectral slope of the electroencephalogram (EEG) estimated in the γ frequency range has been proposed as an arousal marker that differentiates wake, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Here, we sought to replicate and extend these findings in a large sample, providing a comprehensive characterization of how slope changes with age, sex, and its test-retest reliability as well as potential confounds that could affect the slope estimation. We used 10,255 whole-night polysomnograms (PSGs) from the National Sleep Research Resource (NSRR). All preprocessing steps were performed using an open-source Luna package and the spectral slope was estimated by fitting log-log linear regression models on the absolute power from 30 to 45 Hz separately for wake, NREM, and REM stages. We confirmed that the mean spectral slope grows steeper going from wake to NREM to REM sleep. We found that the choice of mastoid referencing scheme modulated the extent to which electromyogenic, or electrocardiographic artifacts were likely to bias 30- to 45-Hz slope estimates, as well as other sources of technical, device-specific bias. Nonetheless, within individuals, slope estimates were relatively stable over time. Both cross-sectionally and longitudinal, slopes tended to become shallower with increasing age, particularly for REM sleep; males tended to show flatter slopes than females across all states. Our findings support that spectral slope can be a valuable arousal marker for both clinical and research endeavors but also underscore the importance of considering interindividual variation and multiple methodological aspects related to its estimation.

Cerebellar Hemorrhage Presented as Torsades de Pointes

<p>A 67-year-old female with a history of hypertension was presented to the emergency department with headache and vomiting. She fell into a coma soon after her arrival and had a cardiac arrest. Cardiopulmonary resuscitation was immediately performed, and epinephrine was given every 3 min. Her initial rhythm was pulseless electrical activity,which later developed into Torsades de Pointes (TdP). However, TdP was misinterpreted as ventricular fibrillation (VF).Amiodarone was given for sustained wide QRS complex arrhythmia. After the return of spontaneous circulation (ROSC),a brain computed tomography scan showed a cerebellar haemorrhage. It may be difficult to distinguish TdP from VF during resuscitation since electrocardiographic artefacts could mislead health care providers. In this case, TdP may be related to catecholamine-induced cardiac injury, brain stem compression or adrenergic effects of epinephrine.Furthermore, this case report emphasises the importance of brain computed tomography for patients who suddenly collapsed in emergency departments; even a lethal arrhythmia was initially noted.</p> <p> </p>

0194 Sources of variation in the spectral slope of the sleep EEG

Abstract Introduction The 1/f spectral slope of the electroencephalogram (EEG) estimated in the gamma frequency range has been shown to reflect neural excitation/inhibition ratio and synchronization level within local neural populations. It was proposed as an arousal marker that differentiates wake, non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. These stages exhibit progressively steeper 30-45 Hz slopes, interpreted in terms of increasing cortical inhibition. Here we sought to replicate these findings in a larger sample and provide a comprehensive characterization of how slope changes with age, sex, and its test-retest reliability as well as potential confounds that could affect the slope estimation. Methods After stringent exclusions and quality control, our final sample included 10,255 whole-night polysomnograms (PSGs) on 7,312 individuals 2,943 of whom had a second PSG, from the National Sleep Research Resource (NSRR). All preprocessing steps were performed using an open-source Luna package and the spectral slope was estimated by fitting log-log linear regression models on the absolute power from 30 to 45 Hz separately for wake, NREM and REM stages. We described sources of variation in the spectral slope (both within and between individuals) and its relationship to other sleep parameters including power and interhemispheric coherence. Results There was unambiguous statistical support for the hypothesis that, within individuals, the mean spectral slope grows steeper going from wake to NREM to REM sleep. We found that the choice of mastoid referencing scheme modulated the extent to which electromyogenic or electrocardiographic artifacts were likely to bias 30-45 Hz slope estimates, as well as other sources of technical, device-specific bias. Nonetheless, within individuals, slope estimates were relatively stable over time. Both cross-sectionally and longitudinal, slopes tended to become shallower with increasing age, particularly for REM sleep; males tended to show flatter slopes than females across all states. Although conceptually distinct, spectral slope did not predict sleep state substantially better than other summaries of the high-frequency EEG power spectrum (>20 Hz, in this context) including beta band power, however. In contrast to the common conception of the REM EEG as relatively wake-like (i.e. ‘paradoxical’ sleep), REM and wake were the most divergent states for multiple metrics, with NREM exhibiting intermediate profiles. Under a simplified modeling framework, changes in spectral slope could not, by themselves, fully account for the observed differences between states, if assuming a strict power-law model. Conclusion Although the spectral slope is appealing, theoretically inspired parameterization of the sleep EEG, we underscore some practical considerations that should be borne in mind when applying it in diverse datasets. Future work will be needed to fully characterize state-dependent changes in the aperiodic portions of the EEG power spectra, which appear to be consistent with, albeit not fully explained by, changes in the spectral slope. Support (If Any)

Bizarre T Waves: What Do They Mean?

Electrocardiographic artifacts are common and may often interfere with interpretation. We describe a case of bizarre appearing T waves. The left arm electrode was placed near a pulsatile fistula, which created an artery pulse tapping artifact. When encountering unexpected electrocardiographic findings, inspection of the electrocardiogram and lead placement may identify the cause. (Level of Difficulty: Intermediate.)

Estimated ECG Subtraction method for removing ECG artifacts in esophageal recordings of diaphragm EMG

The accuracy of diaphragm electromyogram (EMGdi) derived parameters, as used in critically ill intensive care unit (ICU) patients, can be compromised due to electrocardiographic (ECG) interference in the EMGdi signal. Removal of ECG contamination from the esophageal recordings of the EMGdi is challenging due to spectral overlapping of EMG and ECG signals and because of variability in ECG shape and amplitude. Therefore, we designed an Estimated ECG Subtraction (EES) method, based on three steps: (1) identification of the timing of the ECG artifact without an ECG reference channel, (2) estimation of the normalized ECG, considering the EMGdi as noise, and (3) subtraction of the denormalized ECG estimate from the EMGdi recordings. We evaluated the EES method against the use of a single wavelet-based adaptive filter. Using EMGdi signals of ten ICU patients and simulated contaminated EMG, we demonstrated that the EES method yields uncontaminated EMGdi, and showed that it is more effective than a wavelet-based adaptive filter only. Implementation of this technique may offer means to improve diaphragm activity monitoring and control in clinical practice.

Neurostimulator-induced ECG artefacts: A systematic analysis

ObjectivesDeep brain stimulation (DBS) is known to interfere with electrocardiographic (ECG) examinations. In emergency situations, such electrical interferences can not only thwart ECG diagnostics, but even induce an ECG pattern that causes the emergency medical service to initiate inadequate or even harmful therapy. Aim of this prospective study was to evaluate factors influencing ECG interpretation in DBS and to evaluate the susceptibility of ECG criteria ‘frequency’, ‘rhythm’, ‘regularity’, ‘QRS-configuration’, and ‘ST-segment’ on neurostimulation. Patients and methodsIn 33 DBS patients (17 male, 16 female, mean age 64 years), limb-, 12 channel-, Nehb, and adhesive paddle-lead ECG were performed in activated (n = 33) and deactivated (n = 31) stimulation mode during outpatient follow-up examinations. The examinations were carried out using three different ECG devices (two portable emergency ECG-monitor/defibrillation/pacer-devices, one stationary hospital device), resulting in 4096 ECG leads. Statistics have been based on regression analyses and on a maximum likelihood estimation regression model. ResultsMonopolar settings were found to be a relevant factor interfering significantly more often with ECG recording than bipolar parameters (p < 0.0001). Due to recurring movement artefacts, deactivation of bipolar stimulation might even significantly worsen ECG quality (p < 0.0001). Interpretability of ‘rhythm’ (β = −0.088, p = 0.03) and ‘frequency’ (β = −0.110, p = 0.02) revealed significant negative correlation to the applied neurostimulation voltage. Nehb lead yielded in highest ECG interpretability. ConclusionBipolar neurostimulation mode barely affected the ECGs; furthermore, the suppression of motion artefacts by neurostimulation can improve ECG quality. If monopolar neurostimulation is required, at least, stimulation voltage should be as low as possible to obtain good stimulation results.

Loss of Pacer Spikes as electrocardiographic (EKG) Artifact Due to Microdebrider Use During Endoscopic Dacryocystorhinostomy.

As intraoperative use of electronic equipment becomes more common, familiarity with the potential for electrocardiographic artifact generated by these instruments is increasingly important. The authors' patient underwent endoscopic dacryocystorhinostomy under general anesthesia for treatment of acute on chronic dacryocystitis secondary to acquired nasolacrimal duct obstruction. She had previously had pacemaker placement for treatment of sick sinus syndrome and low ejection fraction heart failure, and use of a microdebrider intraoperatively resulted in loss of pacer spikes and interference signal on electrocardiographic leading to placement of a magnet. Post-operatively, examination of the microdebrider cord revealed a tear that likely lead to the artifactual electrocardiographic signal influencing the decision for magnet placement. Although there were no long-term ill effects, placement of the magnet was an unnecessary intervention that may have been avoided by prompt recognition of artifactual changes that may be induced by intraoperative use of electronic instrumentation.

An impedance matching algorithm for common-mode interference removal in vagus nerve recordings

BackgroundThe peripheral nervous system is involved in a multitude of physiological functions. Recording neural signals provides information that can be used by diagnostic bioelectronic medicine devices, closed-loop neuromodulation therapies and other neuroprosthetic applications. The ability to accurately record these signals is challenging, due to the presence of various biological and instrument-related interference sources. New methodWe developed a common-mode interference rejection algorithm based on an impedance matching approach for bipolar cuff electrodes. Two unipolar channels were recorded from the two electrode contacts of a bipolar cuff. The impedance mismatch was estimated and used to correct one of the two channels. ResultsWhen applied to electrocardiographic (ECG) artifacts collected from three mice using CorTec electrodes, the algorithm reduced the interference to noise ratio (INR) over simple subtraction by 12 dB on average. The algorithm also reduced the INR of stimulation artifacts in recordings from three rats collected using flexible electrodes by an additional 2.4 dB. In the same experiments evoked electromyographic (EMG) interference was suppressed by 1.3 dB. Comparison with existing methodsSimple subtraction is the common approach for reducing common-mode interference in bipolar recordings, however impedance mismatches that exist or emerge compromise its efficiency. ConclusionsThe algorithm significantly reduced the common-mode interference from ECG artifacts, stimulation artifacts, and evoked EMG interference, while retaining neural signals, in two animal models and two recording setups. This approach can be used in a variety of different neurophysiological setups to remove common-mode interference from a variety of sources.

Extraction of Evoked Compound Nerve Action Potentials from Vagus Nerve Recordings.

Cervical vagus nerve stimulation (VNS) is a neuromodulation therapy for the treatment of several chronic disorders. The effects of VNS are mediated by activation of nerve fibers of different types. In order to maximize the desired and minimize the undesired effects of VNS, assessing activation of vagal fiber types by VNS is essential. Evoked compound nerve action potentials (CNAPs) are commonly used as a method to estimate vagal fiber activation in the context of neurostimulation. However, vagal CNAPs are frequently contaminated by signals from non-neural sources, like electrocardiography (ECG), stimulus artifacts and evoked electromyographic (EMG) activity. In this study, we present a systematic methodology for suppressing non-neural signals in CNAP recordings from the rat vagus. The methodology involves intravenous infusion of vecuronium under ventilation, for suppressing EMG, and digital and analog signal processing, for suppressing ECG and stimulus artifacts, respectively. We compiled A-, B- and C-type fiber activation profiles with and without this methodology and found that our method significantly increased the reliability of CNAPs. We found that the A-component is obscured by the stimulus artifact, whereas the B- and C-components are frequently contaminated by evoked EMG. We extracted CNAPs evoked by square pulses of different polarities and amplitudes and documented effects consistent with well-established biophysical attributes of VNS.

A template subtraction method for reducing electrocardiographic artifacts in EMG signals of low intensity

Abstract The electromyogram (EMG) has been used in several studies for different areas. Whenever recorded on trunk muscles and close to heart, the EMG may be contaminated by electrocardiographic signal (ECG), which may hamper information based on EMG measures, by either decreasing the median frequency (MDF) or increasing the root mean square value (RMS). Therefore, ECG removal from this contaminated EMG is an issue, but the signal processing task is challenging due to the spectral overlapping of signals. The Butterworth high-pass filter with a 30 Hz cutoff frequency has been considered a suitable removal technique in the literature. However, the frequency band below 30 Hz is strongly attenuated, leading thus to information loss on the EMG. In order to mitigate this problem, a simple template subtraction method is proposed, in which the template is based on the contaminated signal itself. Real contamination and emulated mixtures based in real signals were used and the MDF, RMS, correlation coefficient and Kulback-Leibler divergence were analyzed as performance measures. The performance of the proposed method was compared to a Butterworth high-pass filter and it is shown that the template subtraction method has preserved better the EMG information.

Ventricular tachycardia or artifact?

Electrocardiographic artifacts are extracardiac signals that may alter the electrocardiogram (ECG) generating false diagnoses. These artifacts may simulate pathologies on ECG's in healthy patients and result in long-term unnecessary or even deleterious treatments. On the other hand, to consider an arrhythmia as an artifact, may carry even worse consequences.

Wireless Surface Electromyography and Skin Temperature Sensors for Biofeedback Treatment of Headache: Validation Study with Stationary Control Equipment

Background: The use of wearables and mobile phone apps in medicine is gaining attention. Biofeedback has the potential to exploit the recent advances in mobile health (mHealth) for the treatment of headaches. Objectives: The aim of this study was to assess the validity of selected wireless wearable health monitoring sensors (WHMS) for measuring surface electromyography (SEMG) and peripheral skin temperature in combination with a mobile phone app. This proof of concept will form the basis for developing innovative mHealth delivery of biofeedback treatment among young persons with primary headache. Methods: Sensors fulfilling the following predefined criteria were identified: wireless, small size, low weight, low cost, and simple to use. These sensors were connected to an app and used by 20 healthy volunteers. Validity was assessed through the agreement with simultaneous control measurements made with stationary neurophysiological equipment. The main variables were (1) trapezius muscle tension during different degrees of voluntary contraction and (2) voluntary increase in finger temperature. Data were statistically analyzed using Bland-Altman plots, intraclass correlation coefficient (ICC), and concordance correlation coefficient (CCC). Results: The app was programmed to receive data from the wireless sensors, process them, and feed them back to the user through a simple interface. Excellent agreement was found for the temperature sensor regarding increase in temperature (CCC .90; 95% CI 0.83-0.97). Excellent to fair agreement was found for the SEMG sensor. The ICC for the average of 3 repetitions during 4 different target levels ranged from .58 to .81. The wireless sensor showed consistency in muscle tension change during moderate muscle activity. Electrocardiography artifacts were avoided through right-sided use of the SEMG sensors. Participants evaluated the setup as usable and tolerable. Conclusions: This study confirmed the validity of wireless WHMS connected to a mobile phone for monitoring neurophysiological parameters of relevance for biofeedback therapy.