Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring.

BACKGROUND: Wearable sensors have revolutionized cardiac health monitoring, with Seismocardiography (SCG) at the forefront due to its non-invasive nature. However, the substantial motion artefacts have hindered the translation of SCG-based medical applications, primarily induced by walking. In contrast, our innovative technique, Adaptive Bidirectional Filtering (ABF), surpasses these challenges by refining SCG signals more effectively than any motion-induced noise. ABF leverages a noise-cancellation algorithm, operating on the benefits of the Redundant Multi-Scale Wavelet Decomposition (RMWD) and the bidirectional filtering framework, to achieve optimal signal quality. METHODOLOGY: The ABF technique is a two-stage process that diminishes the artefacts emanating from motion. The first step by RMWD is the identification of the heart-associated signals and the isolating samples with those related frequencies. Subsequently, the adaptive bidirectional filter operates in two dimensions: it uses Time-Frequency masking that eliminates temporal noise while engaging in non-negative matrix Decomposition to ensure spatial correlation and dorsoventral vibration reduction jointly. The main component that is altered from the other filters is the recursive structure that changes to the motion-adapted filter, which uses vertical axis accelerometer data to differentiate better between accurate SCG signals and motion artefacts. OUTCOME: Our empirical tests demonstrate exceptional signal improvement with the application of our ABF approach. The accuracy in heart rate estimation reached an impressive r-squared value of 0.95 at - 20 dB SNR, significantly outperforming the baseline value, which ranged from 0.1 to 0.85. The effectiveness of the motion-artifact-reduction methodology is also notable at an SNR of - 22 dB. Consequently, ECG inputs are not required. This method can be seamlessly integrated into noisy environments, enhancing ECG filtering, automatic beat detection, and rhythm interpretation processes, even in highly variable conditions. The ABF method effectively filters out up to 97% of motion-related noise components within the SCG signal from implantable devices. This advancement is poised to become an integral part of routine patient monitoring.

Neurotransmitter metabolites in milk ferments of Leuconostoc mesenteroides regulate temperature-sensitive heartbeats in an ex ovo model.

Accumulated evidence has supported the probiotic activity of Leuconostoc mesenteroides (L. mesenteroides) which can yield beneficial metabolites via fermentation. Here, bovine milk rich in phenylalanine（PHE) was used as a source for fermentation of L. mesenteroides. The complexes of PHE with bacterial phenylalanine hydroxylase (PheH) at two temperatures were revealed via molecular dynamics simulation. Two carbon hydrogen bonds and a Pi-Alkyl T-shaped interaction were newly formed at an active site of the PheH-PHE complex. The PheH interacted with two different hydrogen atoms in an amine of PHE via conventional hydrogen bonds at 37 °C, a temperature that accelerated the milk fermentation of L. mesenteroides. Twenty-eight metabolites including various neurotransmitters in fermented milk were identified and quantified by liquid chromatography coupled to quadrupole ion trap (Q-Trap) tandem mass spectrometry. Ex ovo injection of milk ferments into the yolk sac of chicken embryos enhanced a rising temperature-induced increase in heartbeats towards the normal resting level. The neurotransmitter-rich milk ferments hold potential for using to adjust energy metabolism, referred from heart rates, during fluctuating temperature conditions.

Should Adolescents Listen to Their Hearts? A Closer Look at the Associations Between Interoception, Emotional Awareness and Emotion Regulation in Adolescents.

The aim of the current study was to replicate findings from prior work among adults showing that individuals with better interoceptive skills have more emotional awareness, and show better emotion regulation abilities, in a sample of adolescents and by relying on instructions that reduce the contamination of known confound variables. A total of 102 Belgian adolescents (Mage = 14.10 years, SDage = .63; 50 males) completed self-report questionnaires of emotional processes (FEEL-KJ and DERS) and the modified heartbeat counting task. From this task, interoceptive accuracy, interoceptive sensibility (confidence ratings), and interoceptive awareness scores (within-person correlations) were derived per participant. Results revealed no associations between the three dimensions of interoception and adolescents' levels of emotional awareness, adaptive, and maladaptive emotion regulation. The lack of associations which contrast some prior work with adults may be due to developmental differences. However, these might also support the low validity of the heartbeat counting task, or could be attributed to the measurement of the emotion measures (i.e., self-report). Future studies should, nevertheless, also test whether these non-significant results can be explained by the developmental differences in adolescents. Longitudinal research is needed to capture interoceptive changes during adolescence, as well as to replicate the current findings using rigorous multimethod approaches that increase the validity of interoception measurement.

Identifying Gravity-Related Artifacts on Ballistocardiography Signals by Comparing Weightlessness and Normal Gravity Recordings (ARTIFACTS): Protocol for an Observational Study.

BACKGROUND: Modern ballistocardiography (BCG) and seismocardiography (SCG) use acceleration sensors to measure oscillating recoil movements of the body caused by the heartbeat and blood flow, which are transmitted to the body surface. Acceleration artifacts occur through intrinsic sensor roll, pitch, and yaw movements, assessed by the angular velocities of the respective sensor, during measurements that bias the signal interpretation. OBJECTIVE: This observational study aims to generate hypotheses on the detection and elimination of acceleration artifacts due to the intrinsic rotation of accelerometers and their differentiation from heart-induced sensor accelerations. METHODS: Multimodal data from 4 healthy participants (3 male and 1 female) using BCG-SCG and an electrocardiogram will be collected and serve as a basis for signal characterization, model modulation, and location vector derivation under parabolic flight conditions from µg to 1.8g. The data will be obtained during a parabolic flight campaign (3 times 30 parabolas) between September 24 and July 25 (depending on the flight schedule). To detect the described acceleration artifacts, accelerometers and gyroscopes (6-degree-of-freedom sensors) will be used for measuring acceleration and angular velocities attributed to intrinsic sensor rotation. Changes in acceleration and angular velocities will be explored by conducting descriptive data analysis of resting participants sitting upright in varying gravitational states. RESULTS: A multimodal data set will serve as a basis for research into a noninvasive and gentle method of BCG-SCG with the aid of low-noise and synchronous 3D gyroscopes and 3D acceleration sensors. Hypotheses will be generated related to detecting and eliminating acceleration artifacts due to the intrinsic rotation of accelerometers and gyroscopes (6-degree-of-freedom sensors) and their differentiation from heart-induced sensor accelerations. Data will be collected entirely and exclusively during the parabolic flights, taking place between September 2024 and July 2025. Thus, as of June 2024, no data have been collected yet. The data will be analyzed until December 2025. The results are expected to be published by June 2026. CONCLUSIONS: The study will contribute to understanding artificial acceleration bias to signal readings. It will be a first approach for a detection and elimination method. TRIAL REGISTRATION: Deutsches Register Klinische Studien DRKS00034402; https://drks.de/search/en/trial/DRKS00034402. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/63306.

Optimal conditions for cryopreservation by vitrification of largemouth bass (Micropterus salmoides) embryos.

The largemouth bass (Micropterus salmoides) is one of the important freshwater aquaculture species in the world. However, due to limitations on introduction scale, high-density farming, inbreeding, and species hybridization, the germplasm resources of largemouth bass face threats such as degradation and susceptibility to diseases. Therefore, it is urgent to conduct research on the conservation of its original and good germplasm resources. We optimized the conditions of cryopreservation to vitrify and revive largemouth bass embryos, including the mixing ratio of cryoprotectants, embryo stage, equilibration step and temperature, and washing regent. The results showed that the least toxic single, binary, and ternary mixed permeating cryoprotectants were PG, PM (PG: MeOH = 2:1), and PMD (PM: DMSO = 3:1), respectively. The least toxic non-permeating cryoprotectant was 5 % glucose. The optimal vitrification solution selected was PMDG (30 % PMD + 5 % glucose) with an 80.67 % survival rate of embryos. Embryos at the heartbeat stage exhibited strong tolerance to the PMDG solution, which is the optimal embryo stage for cryopreservation. During the equilibration process, either the five-step equilibration method or pre-cooling the cryoprotectant to 4°C could reduce its toxicity. During the washing process, a 0.125 mol·L-1 sucrose solution yielded the best results. Based on the optimized conditions, 650 embryos at the heartbeat stage were subjected to cryopreservation by vitrification, resulting in a total of 350 intact transparent eggs, two of which hatched successfully. The results provide a reference for further improving the efficiency of cryopreservation by vitrification of largemouth bass and other fish species.

Testing an artificial intelligence algorithm to predict fetal heartbeat of vitrified-warmed blastocysts from a single image: predictive ability in different settings.

STUDY QUESTION: Could an artificial intelligence (AI) algorithm predict fetal heartbeat from images of vitrified-warmed embryos? SUMMARY ANSWER: Applying AI to vitrified-warmed blastocysts may help predict which ones will result in implantation failure early enough to thaw another. WHAT IS KNOWN ALREADY: The application of AI in the field of embryology has already proven effective in assessing the quality of fresh embryos. Therefore, it could also be useful to predict the outcome of frozen embryo transfers, some of which do not recover their pre-vitrification volume, collapse, or degenerate after warming without prior evidence. STUDY DESIGN, SIZE, DURATION: This retrospective cohort study included 1109 embryos from 792 patients. Of these, 568 were vitrified blastocysts cultured in time-lapse systems in the period between warming and transfer, from February 2022 to July 2023. The other 541 were fresh-transferred blastocysts serving as controls. PARTICIPANTS/MATERIALS, SETTING, METHODS: Four types of time-lapse images were collected: last frame of development of 541 fresh-transferred blastocysts (FTi), last frame of 467 blastocysts to be vitrified (PVi), first frame post-warming of 568 vitrified embryos (PW1i), and last frame post-warming of 568 vitrified embryos (PW2i). After providing the images to the AI algorithm, the returned scores were compared with the conventional morphology and fetal heartbeat outcomes of the transferred embryos (n = 1098). The contribution of the AI score to fetal heartbeat was analyzed by multivariate logistic regression in different patient populations, and the predictive ability of the models was measured by calculating the area under the receiver-operating characteristic curve (ROC-AUC). MAIN RESULTS AND THE ROLE OF CHANCE: Fetal heartbeat rate was related to AI score from FTi (P < 0.001), PW1i (P < 0.05), and PW2i (P < 0.001) images. The contribution of AI score to fetal heartbeat was significant in the oocyte donation program for PW2i (odds ratio (OR)=1.13; 95% CI [1.04-1.23]; P < 0.01), and in cycles with autologous oocytes for PW1i (OR = 1.18; 95% CI [1.01-1.38]; P < 0.05) and PW2i (OR = 1.15; 95% CI [1.02-1.30]; P < 0.05), but was not significantly associated with fetal heartbeat in genetically analyzed embryos. AI scores from the four groups of images varied according to morphological category (P < 0.001). The PW2i score differed in collapsed, non-re-expanded, or non-viable embryos compared to normal/viable embryos (P < 0.001). The predictability of the AI score was optimal at a post-warming incubation time of 3.3-4 h (AUC = 0.673). LIMITATIONS, REASONS FOR CAUTION: The algorithm was designed to assess fresh embryos prior to vitrification, but not thawed ones, so this study should be considered an external trial. WIDER IMPLICATIONS OF THE FINDINGS: The application of predictive software in the management of frozen embryo transfers may be a useful tool for embryologists, reducing the cancellation rates of cycles in which the blastocyst does not recover from vitrification. Specifically, the algorithm tested in this research could be used to evaluate thawed embryos both in clinics with time-lapse systems and in those with conventional incubators only, as just a single photo is required. STUDY FUNDING/COMPETING INTERESTS: This study was supported by the Regional Ministry of Innovation, Universities, Science and Digital Society of the Valencian Community (CIACIF/2021/019) and by Instituto de Salud Carlos III (PI21/00283), and co-funded by European Union (ERDF, 'A way to make Europe'). M.M. received personal fees in the last 5 years as honoraria for lectures from Merck, Vitrolife, MSD, Ferring, AIVF, Theramex, Gedeon Richter, Genea Biomedx, and Life Whisperer. There are no other competing interests. TRIAL REGISTRATION NUMBER: N/A.

Blind individuals' enhanced ability to sense their own heartbeat is related to the thickness of their occipital cortex.

Blindness is associated with heightened sensory abilities, such as improved hearing and tactile acuity. Moreover, recent evidence suggests that blind individuals are better than sighted individuals at perceiving their own heartbeat, suggesting enhanced interoceptive accuracy. Structural changes in the occipital cortex have been hypothesized as the basis of these behavioral enhancements. Indeed, several studies have shown that congenitally blind individuals have increased cortical thickness within occipital areas compared to sighted individuals, but how these structural differences relate to behavioral enhancements is unclear. This study investigated the relationship between cardiac interoceptive accuracy and cortical thickness in 23 congenitally blind individuals and 23 matched sighted controls. Our results show a significant positive correlation between performance in a heartbeat counting task and cortical thickness only in the blind group, indicating a connection between structural changes in occipital areas and blind individuals' enhanced ability to perceive heartbeats.

A novel diagnosis method combined dual-channel SE-ResNet with expert features for inter-patient heartbeat classification.

As the number of patients with cardiovascular diseases (CVDs) increases annually, a reliable and automated system for detecting electrocardiogram (ECG) abnormalities is becoming increasingly essential. Scholars have developed numerous methods of arrhythmia classification using machine learning or deep learning. However, the issue of low classification rates of individual classes in inter-patient heartbeat classification remains a challenge. This study proposes a method for inter-patient heartbeat classification by fusing dual-channel squeeze-and-excitation residual neural networks (SE-ResNet) and expert features. In the preprocessing stage, ECG heartbeats extracted from both leads of ECG signals are filtered and normalized. Additionally, nine features representing waveform morphology and heartbeat contextual information are selected to be fused with the deep neural networks. Using different filter and kernel sizes for each block, the SE-residual block-based model can effectively learn long-term features between heartbeats. The divided ECG heartbeats and extracted features are then input to the improved SE-ResNet for training and testing according to the inter-patient scheme. The focal loss is utilized to handle the heartbeat of the imbalance category. The proposed arrhythmia classification method is evaluated on three open-source databases, and it achieved an overall F1-score of 83.39 % in the MIT-BIH database. This system can be applied in the scenario of daily monitoring of ECG and plays a significant role in diagnosing arrhythmias.

Heartbeat-related spectral perturbation of electroencephalogram reflects dynamic interoceptive attention states in the trial-by-trial classification analysis.

Attending to heartbeats for interoceptive awareness initiates distinct electrophysiological responses synchronized with the R-peaks of an electrocardiogram (ECG), such as the heartbeat-evoked potential (HEP). Beyond HEP, this study proposes heartbeat-related spectral perturbation (HRSP), a time-frequency map of the R-peak locked electroencephalogram (EEG), and explores its characteristics in identifying interoceptive attention states using a classification approach. HRSPs of EEG brain components specified by independent component analysis (ICA) were used for the offline and online classification of interoceptive states. A convolutional neural network (CNN) designed specifically for HRSP was applied to publicly available data from a binary-state experiment (attending to self-heartbeats and white noise) and data from our four-state classification experiment (attending to self-heartbeats, white noise, time passage, and toe) with diverse input feature conditions of HRSP. From the dynamic state perspective, we evaluated the primary frequency bands of HRSP and the minimal number of averaging epochs required to reflect changing interoceptive attention states without compromising accuracy. We also assessed the utility of group ICA and models for classifying HRSP in new participants. The CNN for trial-by-trial HRSP with actual R-peaks demonstrated significantly higher classification accuracy than HRSP with sham, i.e., randomly positioned, R-peaks. Gradient-weighted class activation mapping highlighted the prominent role of theta and alpha bands between 200-600 ms post-R-peak-features absent in classifications using sham HRSPs. Online classification benefits from employing a group ICA and classification model, ensuring reliable accuracy without individual EEG precollection. These results suggest HRSP's potential to reflect interoceptive attention states, proposing transformative implications for clinical applications.

Listen to your heart: Trade-off between cardiac interoceptive processing and visual exteroceptive processing.

Internal bodily signals, such as heartbeats, can influence conscious perception of external sensory information. Spontaneous shifts of attention between interoception and exteroception have been proposed as the underlying mechanism, but direct evidence is lacking. Here, we used steady-state visual evoked potential (SSVEP) frequency tagging to independently measure the neural processing of visual stimuli that were concurrently presented but varied in heartbeat coupling in healthy participants. Although heartbeat coupling was irrelevant to participants' task of detecting brief color changes, we found decreased SSVEPs for systole-coupled stimuli and increased SSVEPs for diastole-coupled stimuli, compared to non-coupled stimuli. These results suggest that attentional and representational resources allocated to visual stimuli vary according to fluctuations in cardiac-related signals across the cardiac cycle, reflecting spontaneous and immediate competition between cardiac-related signals and visual events. Furthermore, frequent coupling of visual stimuli with stronger cardiac-related signals not only led to a larger heartbeat evoked potential (HEP) but also resulted in a smaller color change evoked N2 component, with the increase in HEP amplitude associated with a decrease in N2 amplitude. These findings indicate an overall or longer-term increase in brain resources allocated to the internal domain at the expense of reduced resources available for the external domain. Our study highlights the dynamic reallocation of limited processing resources across the internal-external axis and supports the trade-off between interoception and exteroception.

Non-Contact Measurement of Cardiopulmonary Activity Using Software Defined Radios.

Vital signs are important indicators to evaluate the health status of patients. Channel state information (CSI) can sense the displacement of the chest wall caused by cardiorespiratory activity in a non-contact manner. Due to the influence of clutter, DC components, and respiratory harmonics, it is difficult to detect reliable heartbeat signals. To address this problem, this paper proposes a robust and novel method for simultaneously extracting breath and heartbeat signals using software defined radios (SDR). Specifically, we model and analyze the signal and propose singular value decomposition (SVD)-based clutter suppression method to enhance the vital sign signals. The DC is estimated and compensated by the circle fitting method. Then, the heartbeat signal and respiratory signal are obtained by the modified variational modal decomposition (VMD). The experimental results demonstrate that the proposed method can accurately separate the respiratory signal and the heartbeat signal from the filtered signal. The Bland-Altman analysis shows that the proposed system is in good agreement with the medical sensors. In addition, the proposed system can accurately measure the heart rate variability (HRV) within 0.5m. In summary, our system can be used as a preferred contactless alternative to traditional contact medical sensors, which can provide advanced patient-centered healthcare solutions.

DR.BEAT: Rule-Based Algorithm for SCG Analysis Without ECG Reference.

The DR.BEAT project aims to develop an accelerometer-based, wearable sensor system for measuring ballistocardiographic (BCG) signals, coupled with signal processing and visualization, to support cardiac health monitoring. A rule-based heartbeat detection was developed to enable the derivation of health parameters independent of an existing reference. This paper outlines the algorithm's methodology and provides an initial evaluation of its performance based on seismocardiographic (SCG) measurements obtained from an initial study involving twelve heart-healthy adults. On average, 87.6% of the heartbeats over all measurements, 97.6% of the heartbeats at rest and 71.9% of the heartbeats during physical stress could be detected.

Robust In-Vehicle Signal Quality Assessment Using Multimodal Signal Fusion.

Continuous monitoring of physiological signals such as electrocardiogram (ECG) in driving environments has the potential to reduce the need for frequent health check-ups by providing real-time information on cardiovascular health. However, capturing ECG from sensors mounted on steering wheels creates difficulties due to motion artifacts, noise, and dropouts. To address this, we propose a novel method for reliable and accurate detection of heartbeats using sensor fusion with a bidirectional long short-term memory (BiLSTM) model. Our dataset contains reference ECG, steering wheel ECG, photoplethysmogram (PPG), and imaging PPG (iPPG) signals, which are more feasible to capture in driving scenarios. We combine these signals for R-wave detection. We conduct experiments with individual signals and signal fusion techniques to evaluate the performance of detected heartbeat positions. The BiLSTMs model achieves a performance of 62.69% in the driving scenario city. The model can be integrated into the system to detect heartbeat positions for further analysis.

When the Heart Meets the Mind: Exploring the Brain-Heart Interaction during Time Perception.

Recent studies suggest that time estimation relies on bodily rhythms and interoceptive signals. We provide the first direct electrophysiological evidence suggesting an association between the brain's processing of heartbeat and duration judgment. We examined heartbeat-evoked potential (HEP) and contingent negative variation (CNV) during an auditory duration-reproduction task and a control reaction-time task spanning 4, 8, and 12 s intervals, in both male and female participants. Interoceptive awareness was assessed with the Self-Awareness Questionnaire (SAQ) and interoceptive accuracy through the heartbeat-counting task (HCT). Results revealed that SAQ scores, but not the HCT, correlated with mean reproduced durations with higher SAQ scores associating with longer and more accurate duration reproductions. Notably, the HEP amplitude changes during the encoding phase of the timing task, particularly within 130-270 ms (HEP1) and 470-520 ms (HEP2) after the R-peak, demonstrated interval-specific modulations that did not emerge in the control task. A significant ramp-like increase in HEP2 amplitudes occurred during the duration-encoding phase of the timing but not during the control task. This increase within the reproduction phase of the timing task correlated significantly with the reproduced durations for the 8 s and the 4 s intervals. The larger the increase in HEP2, the greater the under-reproduction of the estimated duration. CNV components during the encoding phase of the timing task were more negative than those in the reaction-time task, suggesting greater executive resources orientation toward time. We conclude that interoceptive awareness (SAQ) and cortical responses to heartbeats (HEP) predict duration reproductions, emphasizing the embodied nature of time.

Single heartbeat ECG authentication: a 1D-CNN framework for robust and efficient human identification.

This study proposes a small one-dimensional convolutional neural network (1D-CNN) framework for individual authentication, considering the hypothesis that a single heartbeat as input is sufficient to create a robust system. A short segment between R to R of electrocardiogram (ECG) signals was chosen to generate single heartbeat samples by enforcing a rigid length thresholding procedure combined with an interpolation technique. Additionally, we explored the benefits of the synthetic minority oversampling technique (SMOTE) to tackle the imbalance in sample distribution among individuals. The proposed framework was evaluated individually and in a mixture of four public databases: MIT-BIH Normal Sinus Rhythm (NSRDB), MIT-BIH Arrhythmia (MIT-ARR), ECG-ID, and MIMIC-III which are available in the Physionet repository. The proposed framework demonstrated excellent performance, achieving a perfect score (100%) across all metrics (i.e., accuracy, precision, sensitivity, and F1-score) on individual NSRDB and MIT-ARR databases. Meanwhile, the performance remained high, reaching more than 99.6% on mixed datasets that contain larger populations and more diverse conditions. The impressive performance demonstrated in both small and large subject groups emphasizes the model's scalability and potential for widespread implementation, particularly in security contexts where timely authentication is crucial. For future research, we need to examine the incorporation of multimodal biometric systems and extend the applicability of the framework to real-time environments and larger populations.

Heartbeat-evoked potentials following voluntary hyperventilation in epilepsy patients: respiratory influences on cardiac interoception.

Introduction: Current evidence indicates a modulating role of respiratory processes in cardiac interoception, yet whether altered breathing patterns influence heartbeat-evoked potentials (HEP) remains inconclusive. Methods: Here, we examined the effects of voluntary hyperventilation (VH) as part of a clinical routine examination on scalp-recorded HEPs in epilepsy patients (N = 80). Results: Using cluster-based permutation analyses, HEP amplitudes were compared across pre-VH and post-VH conditions within young and elderly subgroups, as well as for the total sample. No differences in the HEP were detected for younger participants or across the full sample, while an increased late HEP during pre-VH compared to post-VH was fond in the senior group, denoting decreased cardiac interoceptive processing after hyperventilation. Discussion: The present study, thus, provides initial evidence of breathing-related HEP modulations in elderly epilepsy patients, emphasizing the potential of HEP as an interoceptive neural marker that could partially extend to the representation of pulmonary signaling. We speculate that aberrant CO2-chemosensing, coupled with disturbances in autonomic regulation, might constitute the underlying pathophysiological mechanism behind the obtained effect. Available databases involving patient records of routine VH assessment may constitute a valuable asset in disentangling the interplay of cardiac and ventilatory interoceptive information in various patient groups, providing thorough clinical data to parse, as well as increased statistical power and estimates of effects with higher precision through large-scale studies.

The Contractile Machines of the Heart.

This chapter will describe basic structural and functional features of the contractile apparatus of muscle cells of the heart, namely, cardiomyocytes and smooth muscle cells. Cardiomyocytes form the contractile myocardium of the heart, while smooth muscle cells form the contractile coronary vessels. Both muscle types have distinct properties and will be considered with respect to their cellular appearance (brick-like cross-striated versus spindle-like smooth), arrangement of contractile proteins (sarcomeric versus non-sarcomeric organization), calcium activation mechanisms (thin-filament versus thick-filament regulation), contractile features (fast and phasic versus slow and tonic), energy metabolism (high oxygen versus low oxygen demand), molecular motors (type II myosin isoenzymes with high adenosine diphosphate [ADP]-release rate versus myosin isoenzymes with low ADP-release rates), chemomechanical energy conversion (high adenosine triphosphate [ATP] consumption and short duty ratio versus low ATP consumption and high duty ratio of myosin II cross-bridges [XBs]), and excitation-contraction coupling (calcium-induced calcium release versus pharmacomechanical coupling). Part of the work has been published (Neuroscience - From Molecules to Behavior", Chap. 22, Galizia and Lledo eds 2013, Springer-Verlag; with kind permission from Springer Science + Business Media).

Visualized Lead Selection for Arrhythmia Classification Based on a Lead Activation Heatmap Using Multi-Lead ECGs.

Visualizing the decision-making process is a key aspect of research regarding explainable arrhythmia recognition. This study proposed a visualized lead selection method to classify arrhythmia for multi-lead ECG signals. The proposed method has several advantages, as it uses a visualized approach to select effective leads, avoiding redundant leads and invalid information. It also captures the temporal dependencies of ECG signals and the complementary information between leads. The method deployed a lead activation heatmap (LA heatmap) based on a lead-wise network to select the proper 5 leads from 12-lead ECG heartbeats extracted from the public 2018 Chinese Physiological Signal Challenge database (CPSC 2018 DB), which were then fed into a ResBiTime network combining bidirectional long short-term memory (Bi-LSTM) networks and residual connections for a classification task of nine heartbeat categories (i.e., N, AF, I-AVB, RBBB, PAC, PVC, STD, LBBB, and STE). The results indicate an average precision of 93.25%, an average recall of 93.03%, an average F1-score of 0.9313, and that the proposed method can effectively extract additional information from ECG heartbeat data.

Association Between Gestational Weeks, Initial Maternal Perception of Fetal Movement, and Individual Interoceptive Differences in Pregnant Women: Cross-Sectional Study.

BACKGROUND: Interoception encompasses the conscious awareness of homeostasis in the body. Given that fetal movement awareness is a component of interoception in pregnant women, the timing of initial detection of fetal movement may indicate individual differences in interoceptive sensitivity. OBJECTIVE: The aim of this study is to determine whether the association between the gestational week of initial movement awareness and interoception can be a convenient evaluation index for interoception in pregnant women. METHODS: A cross-sectional study was conducted among 32 pregnant women aged 20 years or older at 22-29 weeks of gestation with stable hemodynamics in the Obstetric Outpatient Department. Interoception was assessed using the heartbeat-counting task, with gestational weeks at the first awareness of fetal movement recorded via a questionnaire. Spearman rank correlation was used to compare the gestational weeks at the first awareness of fetal movement and heartbeat-counting task scores. RESULTS: A significant negative correlation was found between the gestational weeks at the first fetal movement awareness and heartbeat-counting task performance among all participants (r=-0.43, P=.01) and among primiparous women (r=-0.53, P=.03) but not among multiparous women. CONCLUSIONS: Individual differences in interoception appear to correlate with the differences observed in the timing of the first awareness of fetal movement.

Intranasal Oxytocin Improves Interoceptive Accuracy and Heartbeat-Evoked Potentials During a Cardiac Interoceptive Task.

BACKGROUND: Interoception represents perception of the internal bodily state, which is closely associated with social/emotional processing and physical health in humans. Understanding the mechanism that underlies interoceptive processing, particularly its modulation, is therefore of great importance. Given the overlap between oxytocinergic pathways and interoceptive signaling substrates in both peripheral visceral organs and the brain, intranasal oxytocin administration is a promising approach for modulating interoceptive processing. METHODS: Using a double-blind, placebo-controlled, between-participant design, we recruited 72 healthy male participants who performed a cardiac interoceptive task during electroencephalograph and electrocardiograph recording to examine whether intranasal administration of the neuropeptide oxytocin could modulate interoceptive processing. We also collected data in a resting state to examine whether we could replicate previous findings. RESULTS: The results showed that in the interoceptive task, oxytocin increased interoceptive accuracy at the behavioral level, which was paralleled by larger heartbeat-evoked potential amplitudes in frontocentral and central regions on the neural level. However, there were no significant effects of oxytocin on electroencephalograph or electrocardiograph during resting state. CONCLUSIONS: These findings suggest that oxytocin may only have a facilitatory effect on interoceptive processing under task-based conditions. Our findings not only provide new insights into the modulation of interoceptive processing via targeting the oxytocinergic system but also provide proof-of-concept evidence for the therapeutic potential of intranasal oxytocin in mental disorders with dysfunctional interoception.