Miracle-dz/UniFAR-FTUs huggingface dataset:
The Shape of Things to Come in Speech Production: A Functional Magnetic Resonance Imaging Study of Visual Form Interference during Lexical Access

Studies of context effects in speech production have shown that semantic feature overlap produces interference in naming of categorically related objects. In neuroimaging studies, this semantic interference effect is consistently associated with involvement of left superior and middle temporal gyri. However, at least part of this effect has recently been shown to be attributable to visual form similarity, as categorically related objects typically share visual features. This fMRI study examined interference produced by visual form overlap in the absence of a category relation in a picture–word interference paradigm. Both visually similar and visually dissimilar distractors led to increased BOLD responses in the left inferior frontal gyrus compared with the congruent condition. Naming pictures in context with a distractor word denoting an object visually similar in form slowed RTs compared with unrelated words and was associated with reduced activity in the left posterior middle temporal gyrus. This area is reliably observed in lexical level processing during language production tasks. No significant differential activity was observed in areas typically engaged by early perceptual or conceptual feature level processing or in areas proposed to be engaged by postlexical language processes, suggesting that visual form interference does not arise from uncertainty or confusion during perceptual or conceptual identification or after lexical processing. We conclude that visual form interference has a lexical locus, consistent with the predictions of competitive lexical selection models.
Investigating Phasic Activity of Time-Varying High-Order Spectra: A Heartbeat Dynamics Study During Cold-Pressor Test

Recent modeling advances have successfully derived time-varying estimates of nonlinear heartbeat dynamics, whose quantifiers mainly rely on first-order moments (i.e., average over time). While, these metrics account for the information carried by the tonic (slow trend) nonlinear dynamics, they fail to quantify potentially meaningful information nested in the superimposed phasic (high-frequency) activity of the physiological series. In this study, we investigate new metrics from phasic activity of time-varying bispectral indexes, which are derived from nonlinear point-process modeling of heartbeat dynamics. Instantaneous phasic activity is derived using wavelet decomposition of time-varying bispectral power, and quantified using the area under the curve (AUC) and variance (VAR) metrics. Results, gathered from ECG series from 22 healthy volunteers undergoing cold-pressor test (CPT), show that phasic components of low-frequency (LL) instantaneous bispectra significantly change between resting and CPT states, as quantified by AUC and VAR. In conclusion, phasic activations of bispectral estimates carry meaningful information for the nonlinear assessment of sympatho-vagal regulation onto the heart. This study poses a foundation for a novel signal processing framework investigating time-varying estimates of nonlinear cardiovascular control.
Effects of the β-Adrenoceptor Blocker Carvedilol in Short QT Syndrome Caused by N588K Mutation in HERG: A Simulation Study

The short QT syndrome (SQTS) is associated with shortening of QT interval resulting from an accelerated cardiac repolarization. The SQT1, SQTS variant, results from a gain-of-function N588K-KCNH2 mutation in the rapid delayed rectifier potassium current $(I_{Kr})$ channels. Since $\beta$ - Adrenoceptor blocker can block slow delayed rectifier potassium currents $(I_{Ks)}$ and $I_{Kr}$ we used in silico approach to evaluate carvedilol's effects on SQT1. Mathematical models of human ventricular action potential (AP) developed by ten Tusscher et al. were modified to incorporate a Markov chain formulation of $I_{Kr}$ describing the SQT1 mutant condition. AP models were incorporated into a transmural strand for investigation of QT interval changes. In addition, the simulated $I_{Ks}$ and $I_{Kr}$ inhibition to prolong the QT interval in SQT1 was quantified. The blocking effects of carvedilol on $I_{Ks}$ and $I_{Kr}$ were modelled by using Hill coefficient and $IC_{50}$ from literatures (10 μ M carvedilol reduced $I_{Kr}$ in Wild Type- and N588K-KCNH2 by 92.8% and 36.0%; it reduced $I_{Ks}$ by 36.5% in both conditions). At single cell level, carvedilol prolonged the AP duration (APD) in SQT1; at strand level, the effects of carvedilol normalized the QT interval in SQT1 from 286 ms to 364 ms. Simulations identified $\beta$ - Adrenoceptor blocker carvedilol as a potential drug for SQTS treatment.
Heartbeat Detection Using Three-Axial Seismocardiogram Acquired by Mobile Phone

Recent studies have demonstrated the possibility to acquire the heartbeat induced vibrations resembling the seismocardiogram (SCG) by the mobile phone accelerometer (m-SCG). As most of ECG-free beat detection algorithms are based on processing one m-SCG component only (e.g. head-to-foot), our aim was to propose an alternative and robust method to extract beat-to-beat systolic complex (SC) from three-axial m-SCG and test its occurrence compared to R peak of ECG. Eleven male subjects (mean age 22±3) were recruited and m-SCG signal (50 Hz) was acquired for 5 minutes by a smartphone positioned on the chest. Newtonian equations of kinematics and continuous wavelet transform were applied to the m-SCG signal to detect beat-by-beat SC occurrence. Data from one subject were discarded due to low quality signal (feasibility 91%). High values of sensitivity (0.995), positive predictive value (0.974) and accuracy (0.96) were obtained. The explored heart rate range (45–101 bpm) was quite wide and acceptable limits of agreement (±1 - ±6 bpm) were achieved.
AF Detection by Exploiting the Spectral and Temporal Characteristics of ECG Signals With the LSTM Model

This research reinvestigates the detection of atrial fibrillation (AF) from a recurrent neural network (RNN) viewpoint. In particular, a long short-term memory (LSTM) model of RNN is designed to exploit the high-order spectral and temporal features of the multi-lead electrocardiogram (ECG) signals of patients with AF. To verify the proposed method, the LSTM model is tested with ECG data available from the PhysioNet and some normal ECG data collected in our labs. The results show that not only the deviation of the so-called RR intervals of ECG signals but also its temporal variations are critical to AF detection. The accuracy of AF detection can reach up to 98.3 %, with an LSTM model of using 30 hidden units. Considering more realistic applications, we further tested the model with subjects different from that of the training data. The accuracy is about 87% with high sensitivity. The experimental results show that the proposed model is able to effectively extract both the long-term and short-term characteristics of the spectral content of the AF ECG signals, making it a good candidate model for AF detection.
Force-Interval Relationships of the Heart Measured With Photoplethysmography During Atrial Fibrillation

Force-interval relationships (FIRs) of the heart represent the relationships between inter-beat intervals (IBIs) and strength of the ventricular contractions. These relationships are typically measured invasively and are altered from normal in heart failure (HF). An unobtrusive and continuous measurement of FIRs could be beneficial when HF and atrial fibrillation (AF) coexist in order to understand if AF causes progression of HF. We hypothesize that FIRs could be assessed during AF with IBIs and hemodynamic changes captured unobtrusively by photo-plethysmography (PPG) at the wrist. FIRs were assessed by using Spearman's rank correlation between the pulse onset change in the PPG waveform and either the preceding or pre-preceding IBIs $(r_{pre}\ and\ r_{pre-pre})$ in 5-minute segments. 32 patients (14 continuous AF, 18 no AF) were measured during the night with PPG and electrocardiography as a reference. The mean and standard deviation of $r_{pre}$ were $-0.25\pm 0.08$ and $0.05\pm 0.12(p < 0.0001)$, and of $r_{pre-pre} 0.60\pm 0.09$ and $0.16\pm 0.14 (p < 0.0001)$, during AF and sinus rhythm, respectively. Areas under the Receiver Operating Characteristics curve were 0.987 and 0.998, respectively. Thus, during AF the IBIs correlate with the beat-to-beat changes of blood volume measured with PPG, likely to indicate that FIRs can be measured unobtrusively with the PPG signal.
Application of Joint Notch Filtering and Wavelet Transform for Enhanced Powerline Interference Removal in Atrial Fibrillation Electrograms

Analysis of intra-atrial electrograms (EGMs) nowadays constitutes the most common way to gain new insights about the mechanisms triggering and maintaining atrial fibrillation (AF). However, these recordings are highly contaminated by powerline interference (PLI) due to the large amount of electrical devices operating simultaneously in the electrophysiology laboratory. To remove this perturbation, conventional notch filtering has been widely used. However, this method adds artificial fractionation to the EGMs, thus concealing their accurate interpretation. Hence, the development of novel algorithms for PLI suppression in EGMs is still an unresolved challenge. Within this context, the present work introduces the joint application of common notch filtering and Wavelet denoising for enhanced PLI removal in AF EGMs. The algorithm was validated on a set of 100 unipolar EGM signals, which were synthesized with different noise levels. Original and denoised EGMs were compared in terms of a signed correlation index (SCI), computed both in time and frequency domains. Compared with the single use of notch filtering, improvements between 4 and 15% were reached with Wavelet denoising in both domains. As a consequence, the proposed algorithm was able to efficiently reduce high levels of PLI and simultaneously preserve the original morphology of AF EGMs.
Analysis of Panoramic Propagation Patterns Mapped From Patients With Persistent Atrial Fibrillation

The purpose of this study is to analyze the electrical propagation patterns from patients with persistent atrial fibrillation (AF). Unipolar electrograms $(\sim 1$ minute) were recorded sequentially in atrial chambers from 5 patients with persistent AF prior to ablation using a 64-electrode basket catheter. Raw unipolar signals were processed using a suite of signal processing approaches including: 1) A Savitzky-Golay filter, 2) a standard QRS subtraction and 3) a local variability approach which uses a local integral to enhance the signals. Recurring patterns of electrode activation and AF drivers were then identified by using activation time maps and dominant frequency analysis, and by screening through the entire isopotential movies of each basket recording. Localized sources in the form of either localized reentries $(N=1)$ or focal impulses $(N=4)$ were observed in all of the patients studied. Interestingly, all localized sources were found in the left atrium (LA) near the pulmonary veins with the exception of 1 patient where an additional focal impulse was also detected in the right atrium (RA). Disorganized activity was observed in the RA of 3 patients, though their respective LAs were driven by localized sources. These results suggest that either localized sources in the LA or disorganized activity in the RA or both of these mechanisms may be the predominant triggers of persistent AF
ECG-Based Monitoring of Electrolyte Fluctuations During the Long Interdialytic Interval

Hemodialysis (HD) patients have a higher risk of sudden death due to cardiac arrhythmias, which commonly occur during the long interdialytic interval (LII) as a result of electrolyte fluctuations (EFs). Noninvasive monitoring of EFs would enable restoring normal serum electrolyte levels (SELs) by performing early HD before the onset of arrhythmias. In this study, we propose an ECG-derived descriptor, θ µ, that is noise robust and capable of capturing EFs during HD and the LII. To investigate the variation of θ µ, ECG and blood samples of 3 patients were acquired continuously, starting at Friday's HD and ending at Monday's HD. Results show that the increase of θ µ during Friday's HD is correlated with the decrease of SELs. Moreover, θ µ tends to decrease during the LII (no blood samples were obtained) and further increases during Monday's HD. If results in larger databases are confirmed, θ µ might be suitable for noninvasive monitoring of EFs during the LII.
Intrinsic Complexity of RR and QT Intervals at the Cellular Level

We characterize the complexity of interbeat intervals (IBIs) and field potential durations (FPDs) of human-induced plurioptent stem cell-derived cardiomyocytes (hiPSC-CMs). The complexity is assessed using the multiscale entropy (MSE) method up to the scale of ten beats. The MSE profiles of healthy and diseased (long-QT syndrome) hiPSC-CMs show important differences, which demonstrate the usefulness of the method in the characterization of the cells and in the analysis of hereditary cardiac diseases. We show that the intrinsic complexity is possibly altered by the differentiation methods, as well as the age and mutations of the cells.
A Novel Algorithm for Full-Automatic Multipurpose ECG Delineation

Obtaining high accurate wave segmentation or delineation on ECG signals is extremely essential for automatic, semiautomatic and manual ECG interpretation and diagnostics. In this works, a new high accurate and efficient method of detection and delineation of QRS complexes, P waves and T waves in single-channel and multi-channel ECG signals including the standard 12-1ead ECG is presented.
CATERING STRATEGY: A STUDY OF HANIF RAJPUT

Sher Khan folded his jai namaz mat presented years ago by his mentor Hanif Rajput and got ready for his daily chores. He is a driver of one of the many catering vans possessed by Hanif Rajput Caterers. Putting on his jacket with HR block printed on its back he got behind the wheels and headed towards the kitchens to load the cuisine and head for the KMC Gardens where it had to be delivered for the wedding party of one of the clients. He rolled out with many other vans from the kitchen located in KMC sport complex at 7 PM. The traffic was heavy tonight however he managed to reach the DHA Gardens at 8.30 PM. He offloaded the “dhegs”; Mohammad Khan an old crony of his meticulously checked the contents with the Tally Card and signed the receipt. Meanwhile Sher Khan looked at the Gardens, which were cloaked with shamianas and blazing with fancy lights. It was too early for guests but there seemed a lot of hustle and bustle in the vicinity. The stage decorators were in their last phase plugging in the orchids and roses around the podium, waiters were putting the spirit lamps under the dishes and carpets were being swept. He thought of the day when his daughter got a similar wedding treat from the company five years ago, which was funded by Hanif sahib! Mohammad Khan refocused his attention by delivering the receipt, which he pocketed and looked up his next call station. He had to go to KMC Gardens and pick up the shamianas and chairs of last evening’s function and offload them at a business tycoon’s residence in Bath Island. By the time all his chores were over it was well past 2AM and Sher Khan parked his van and took the M17 coach and headed for his home in Balouch Colony.
Intrauterine Growth Restriction Induced ECG Morphological Differences Measured in Adulthood

Numerous studies associate intrauterine growth restriction (IUGR) and premature birth with higher risk for cardiovascular diseases throughout adulthood. This study aims to describe changes at the surface ECG and observe if the results corroborate those correspondences found in previous studies of pre-adolescents who were born with low birthweight. 87 adults conformed the study population. There were 2 subgroups to study: term birth with adequate weight for gestational age (control group, 33 subjects), and those who had IUGR at birth (54 subjects). Once QRS and T-wave loops were obtained from the averaged vectorcardiogram, the angle between the depolarization and repolarization dominant vectors in the three-dimensional space and the absolute and relative angles between the dominant vectors and the three orthogonal planes were studied. The angle between the dominant vectors of the QRS loop and the T-wave loop in the XY-plane (i.e. the frontal plane) showed statistically significant larger values for controls (13.49±13.65) than for adults who were born with IUGR (9.26±8.47). This narrowing can be hypothesised to be a biomarker for IUGR cardiovascular risk. The results are in accordance with those obtained for pre-adolescent subjects who were preterm, further supporting the findings.
Inhomogeneous HRV Spectral Complexity: a Preliminary Evaluation With Gravitational Stimuli Under Selective Autonomic Blockade

Nonlinear Heart Rate Variability (HRV) analysis has been successfully applied to assess autonomic nervous system (ANS) regulation of the cardiovascular system in health and disease. Here, the spectral complexity framework is introduced for characterization of time-varying HRV spectral components. Correlation dimension, D2, and maximum approximate entropy ApEnmax, were calculated on time-varying HRV spectral series derived from a linear point-process model, which was fitted to RR series from 14 healthy subjects undergoing selective ANS blockade during postural changes. Complexity quantification of the instantaneous LF component using D2 revealed significantly higher values in standing vs. supine under atropine (vagal blockade), but not under propranolol (sympathetic blockade), in contrast to the results found under control conditions. Similar trends were found for ApEnmax. Conversely, no statistically significant differences were found in the complexity indices evaluated for the instantaneous HF component, either for standing vs. supine or blockades vs. control. The proposed framework enriches the current knowledge on complex ANS regulation of the heart, supporting the fact that previously reported reduction in cardiovascular complexity during postural changes is mainly vagally driven.
T-Wave Alternans in Partial Epileptic Patients

Epilepsy is a chronic neurological disorder, hallmark of which is unpredictable epileptic seizures (ES). The leading cause of death in people with uncontrolled ES is the sudden unexpected death in epilepsy (SUDEP), which is believed to share genes with sudden cardiac death (SCD). Being T-wave alternans (TWA) an ECG index of SCD, aim of this work was to evaluate TWA occurrence in proximity of ES. Electrocardiograms (ECG) from five partial epileptic patients constituting the “Post-Ictal Heart Rate Oscillations in Partial Epilepsy” Database by Physionet were analysed for automatic TWA identification by the heart-rate adaptive match filter (HRAMF). ES onsets and offsets were annotated. ECG segments starting 10min before ES and ending 10min after ES were extracted and further processed to characterize trends of median heart rate, median TWA (mTWA) and maximum TWA (MTWA) in ES proximity. Levels of mTWA were significantly higher than what previously observed in a female healthy population in all ES (46[25; 59]μV), pre-ES (31 [25;62]μ V) and post-ES (30[26;63]μ V) conditions. Both mTWA and MTWA tended to increase during ES. Thus, in proximity of ES, our epileptic patients are at increased risk of SCD, possibly associated with SUDEP. Other studies defining TWA role as a biomarker for SUDEP are needed.
A Heterogeneous Formulation of the Himeno et al Human Ventricular Myocyte Model for Simulation of Body Surface ECGs

Current multi-scale electrophysiology models capture the processes underlying ECG genesis under physiological and many disease conditions with high fidelity. However, proper representation of the extracellular milieu remains challenging. The human ventricular myocyte model by Himeno et al. is one of the first which faithfully represents the dependence of the action potential (AP) duration on the extracellular calcium concentration ([Ca2+]o). Here, we present a heterogeneous formulation of the Himeno et al. cellular model and integrate it into a multi-scale framework to compute body surface ECGs. We propose 3 variants to account for transmural heterogeneity informed by experimental data and tuned to match AP level features such as repolarization stability. As shown before, an apico-basal gradient of IKs conductance is a likely mechanism causing concordant T-waves. Therefore, we increased IKs in the Himeno et al. model at the apex by a factor of 3.5 compared to the base to obtain an APD shortening of 12.5%. The setup comprising transmural and apico-basal heterogeneity yielded a physiological ventricular ECG. Our novel setup allows to study, for the first time, how realistic changes of the AP under hypo- and hypercalcaemic conditions translate to changes in the ECG. Resulting QT prolongation under hypocalcaemic conditions matched human experimental data.
Comparison of Pediatric and Adult ECG Rhythm Analysis by Automated External Defibrillators During Out-of-Hospital Cardiac Arrest

This study validates the performance of a commercial automated external defibrillator (AED) on pediatric out-of-hospital cardiac arrest interventions. It shows that the AED with settings validated for adults does not worsen its performance in children, except for rapid non-shockable rhythms (−2%). Further, this study compares 14 behavioral ECG characteristics (6 morphological, 4 band-pass QRS filter, 4 spectral) on adult and pediatric rhythms, highlighting significant rhythm-specific changes. Discriminant models trained on adults and tested on pediatrics highlight 6 features with the most powerful AUC>0.9 and the most robust AUC (Pediatric-Adult)>−0. 025. The design of AED shock advisory algorithm, equally safe for adults and pediatrics is possible if the embedded ECG analysis features fulfil the above criteria.
Automated Detection of Sleep Arousals From Polysomnography Data Using a Dense Convolutional Neural Network

In this work, a dense recurrent convolutional neural network (DRCNN) was constructed to detect sleep arousals using available Polysomnography (PSG) measurement channels provided in the 2018 Physionet challenge database. Our model structure is composed of multiple dense convolutional units (DCU) followed by a bidirectional long-short term memory (LSTM) layer followed by a softmax output layer. The sleep events including sleep stages, arousal regions and multiple types of apnea-hypopnea/normal are manually annotated in 2018 Physionet challenge database which enable us to train our proposed network using a multi-task learning mechanism. Three binary cross-entropy loss functions corresponding to sleep/wake, arousal presence/absence and apnea/hypopnea presence/absence detections are summed up to generate our overall network loss function that is optimized using the Adam method. Our model performance was evaluated using two metrics: the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUROC). To measure our model generalization, 4-fold cross-validation was also performed. For training, full night recording data was applied to our model. Finally, our proposed algorithm achieves the first place in the official stage of the Physionet challenge with AUPRC of 0.54 on the blind testing dataset.