Brain-heart interaction disruption in major depressive disorder: disturbed rhythm modulation of the cardiac cycle on brain transient theta bursts.

Brain neurons support arousal and cognitive activity in the form of spectral transient bursts and cooperate with the peripheral nervous system to adapt to the surrounding environment. However, the temporal dynamics of brain-heart interactions have not been confirmed, and the mechanism of brain-heart interactions in major depressive disorder (MDD) remains unclear. This study aimed to provide direct evidence for brain-heart synchronization in temporal dynamics and clarify the mechanism of brain-heart interaction disruption in MDD. Eight-minute resting-state (closed eyes) electroencephalograph and electrocardiogram signals were acquired simultaneously. The Jaccard index (JI) was used to measure the temporal synchronization between cortical theta transient bursts and cardiac cycle activity (diastole and systole) in 90 MDD patients and 44 healthy controls (HCs) at rest. The deviation JI was used to reflect the equilibrium of brain activity between diastole and systole. The results showed that the diastole JI was higher than the systole JI in both the HC and MDD groups; compared to HCs, the deviation JI attenuated at F4, F6, FC2, and FC4 in the MDD patients. The eccentric deviation JI was negatively correlated with the despair factor scores of the HAMD, and after 4 weeks of antidepressant treatment, the eccentric deviation JI was positively correlated with the despair factor scores of the HAMD. It was concluded that brain-heart synchronization existed in the theta band in healthy individuals and that disturbed rhythm modulation of the cardiac cycle on brain transient theta bursts at right frontoparietal sites led to brain-heart interaction disruption in MDD.

Contactless Technologies, Sensors, and Systems for Cardiac and Respiratory Measurement during Sleep: A Systematic Review.

Sleep is essential to physical and mental health. However, the traditional approach to sleep analysis-polysomnography (PSG)-is intrusive and expensive. Therefore, there is great interest in the development of non-contact, non-invasive, and non-intrusive sleep monitoring systems and technologies that can reliably and accurately measure cardiorespiratory parameters with minimal impact on the patient. This has led to the development of other relevant approaches, which are characterised, for example, by the fact that they allow greater freedom of movement and do not require direct contact with the body, i.e., they are non-contact. This systematic review discusses the relevant methods and technologies for non-contact monitoring of cardiorespiratory activity during sleep. Taking into account the current state of the art in non-intrusive technologies, we can identify the methods of non-intrusive monitoring of cardiac and respiratory activity, the technologies and types of sensors used, and the possible physiological parameters available for analysis. To do this, we conducted a literature review and summarised current research on the use of non-contact technologies for non-intrusive monitoring of cardiac and respiratory activity. The inclusion and exclusion criteria for the selection of publications were established prior to the start of the search. Publications were assessed using one main question and several specific questions. We obtained 3774 unique articles from four literature databases (Web of Science, IEEE Xplore, PubMed, and Scopus) and checked them for relevance, resulting in 54 articles that were analysed in a structured way using terminology. The result was 15 different types of sensors and devices (e.g., radar, temperature sensors, motion sensors, cameras) that can be installed in hospital wards and departments or in the environment. The ability to detect heart rate, respiratory rate, and sleep disorders such as apnoea was among the characteristics examined to investigate the overall effectiveness of the systems and technologies considered for cardiorespiratory monitoring. In addition, the advantages and disadvantages of the considered systems and technologies were identified by answering the identified research questions. The results obtained allow us to determine the current trends and the vector of development of medical technologies in sleep medicine for future researchers and research.

Renal Denervation Helps Preserve the Ejection Fraction by Preserving Endocardial-Endothelial Function during Heart Failure.

Renal denervation (RDN) protects against hypertension, hypertrophy, and heart failure (HF); however, it is not clear whether RDN preserves ejection fraction (EF) during heart failure (HFpEF). To test this hypothesis, we simulated a chronic congestive cardiopulmonary heart failure (CHF) phenotype by creating an aorta-vena cava fistula (AVF) in the C57BL/6J wild type (WT) mice. Briefly, there are four ways to create an experimental CHF: (1) myocardial infarction (MI), which is basically ligating the coronary artery by instrumenting and injuring the heart; (2) trans-aortic constriction (TAC) method, which mimics the systematic hypertension, but again constricts the aorta on top of the heart and, in fact, exposes the heart; (3) acquired CHF condition, promoted by dietary factors, diabetes, salt, diet, etc., but is multifactorial in nature; and finally, (4) the AVF, which remains the only one wherein AVF is created ~1 cm below the kidneys in which the aorta and vena cava share the common middle-wall. By creating the AVF fistula, the red blood contents enter the vena cava without an injury to the cardiac tissue. This model mimics or simulates the CHF phenotype, for example, during aging wherein with advancing age, the preload volume keeps increasing beyond the level that the aging heart can pump out due to the weakened cardiac myocytes. Furthermore, this procedure also involves the right ventricle to lung to left ventricle flow, thus creating an ideal condition for congestion. The heart in AVF transitions from preserved to reduced EF (i.e., HFpEF to HFrEF). In fact, there are more models of volume overload, such as the pacing-induced and mitral valve regurgitation, but these are also injurious models in nature. Our laboratory is one of the first laboratories to create and study the AVF phenotype in the animals. The RDN was created by treating the cleaned bilateral renal artery. After 6 weeks, blood, heart, and renal samples were analyzed for exosome, cardiac regeneration markers, and the renal cortex proteinases. Cardiac function was analyzed by echocardiogram (ECHO) procedure. The fibrosis was analyzed with a trichrome staining method. The results suggested that there was a robust increase in the exosomes' level in AVF blood, suggesting a compensatory systemic response during AVF-CHF. During AVF, there was no change in the cardiac eNOS, Wnt1, or ß-catenin; however, during RDN, there were robust increases in the levels of eNOS, Wnt1, and ß-catenin compared to the sham group. As expected in HFpEF, there was perivascular fibrosis, hypertrophy, and pEF. Interestingly, increased levels of eNOS suggested that despite fibrosis, the NO generation was higher and that it most likely contributed to pEF during HF. The RDN intervention revealed an increase in renal cortical caspase 8 and a decrease in caspase 9. Since caspase 8 is protective and caspase 9 is apoptotic, we suggest that RDN protects against the renal stress and apoptosis. It should be noted that others have demonstrated a role of vascular endothelium in preserving the ejection by cell therapy intervention. In the light of foregoing evidence, our findings also suggest that RDN is cardioprotective during HFpEF via preservation of the eNOS and accompanied endocardial-endothelial function.

HeartCV: a tool for transferrable, automated measurement of heart rate and heart rate variability in transparent animals.

Heart function is a key component of whole-organismal physiology. Bioimaging is commonly, but not exclusively, used for quantifying heart function in transparent individuals, including early developmental stages of aquatic animals, many of which are transparent. However, a central limitation of many imaging-related methods is the lack of transferability between species, life-history stages and experimental approaches. Furthermore, locating the heart in mobile individuals remains challenging. Here, we present HeartCV: an open-source Python package for automated measurement of heart rate and heart rate variability that integrates automated localization and is transferrable across a wide range of species. We demonstrate the efficacy of HeartCV by comparing its outputs with measurements made manually for a number of very different species with contrasting heart morphologies. Lastly, we demonstrate the applicability of the software to different experimental approaches and to different dataset types, such as those corresponding to longitudinal studies.

Wearable Fabric Loop Sensor Based on Magnetic-Field-Induced Conductivity for Simultaneous Detection of Cardiac Activity and Respiration Signals.

In this study, a noncontact fabric loop sensor based on magnetic-field-induced conductivity, which can simultaneously detect cardiac activity and respiration signals, was developed and the effects of the sensor's shape and measurement position on the sensing performance were analyzed. Fifteen male subjects in their twenties wore sleeveless shirts equipped with various types of fabric loop sensors (spiky, extrusion, and spiral), and the cardiac activity and respiratory signals were measured twice at positions P2, P4, and P6. The measurements were verified by comparing them against the reference electrocardiogram (ECG) and respiratory signals measured using BIOPAC® (MP150, ECG100B, RSP100C). The waveforms of the raw signal measured by the fabric loop sensor were filtered with a bandpass filter (1-20 Hz) and qualitatively compared with the ECG signal obtained from the Ag/AgCI electrode. Notwithstanding a slight difference in performance, the three fabric sensors could simultaneously detect cardiac activity and respiration signals at all measurement positions. In addition, it was verified through statistical analysis that the highest-quality signal was obtained at the measurement position of P4 or P6 using the spiral loop sensor.

Effect of Visually Induced Motion Sickness from Head-Mounted Display on Cardiac Activity.

Head-mounted display (HMD) virtual reality devices can facilitate positive experiences such as co-presence and deep immersion; however, motion sickness (MS) due to these experiences hinders the development of the VR industry. This paper proposes a method for assessing MS caused by watching VR content on an HMD using cardiac features. Twenty-eight undergraduate volunteers participated in the experiment by watching VR content on a 2D screen and HMD for 12 min each, and their electrocardiogram signals were measured. Cardiac features were statistically analyzed using analysis of covariance (ANCOVA). The proposed model for classifying MS was implemented in various classifiers using significant cardiac features. The results of ANCOVA reveal a significant difference between 2D and VR viewing conditions, and the correlation coefficients between the subjective ratings and cardiac features have significant results in the range of -0.377 to -0.711 (for SDNN, pNN50, and ln HF) and 0.653 to 0.677 (for ln VLF and ln VLF/ln HF ratio). Among the MS classification models, the linear support vector machine achieves the highest average accuracy of 91.1% (10-fold cross validation) and has a significant permutation test outcome. The proposed method can contribute to quantifying MS and establishing viewer-friendly VR by determining its qualities.

Treatment of left tubal pregnancy with foetal cardiac activity using a two-dose methotrexate regimen.

The incidence of ectopic pregnancy (EP) is about 1.3-2.4%. Approximately 6% of maternal deaths in the first trimester occur following ruptured EP. A 35-year-old lady, G4, P3, pregnant 7 weeks + 2 days, presented with left iliac pain, after positive pregnancy test, and ß-human chorionic gonadotropin (ß-hCG) 3614 mIU/ml. The transvaginal sonography showed an empty uterus, with a well-defined left adnexal echogenic structure measuring 38×32 mm (left adnexal gestational sac - GS) with foetal pole (bagel sign). The colour Doppler examination showed foetal cardiac activity with circumferential Doppler flow around the GS (ring of fire). She was diagnosed as left undisturbed tubal pregnancy with foetal cardiac activity. She refused the option of laparoscopic surgery. Therefore, she was counselled for medical treatment using methotrexate (MTX). She was also informed that the MTX treatment may fail due to the presence of foetal cardiac activity, and she may need more than one MTX dose. She received the first MTX dose at an initial ß-hCG 3614 mIU/ml. The fourth day ß-hCG after the first MTX dose was 5421 mIU/ml, while the seventh day ß-hCG was 5055 mIU/ml [< 15% decrease of ß-hCG (6.75%)]; therefore, she was given a second MTX dose. The fourth day ß-hCG after the second MTX dose was 3851 mIU/ml, while the seventh day ß-hCG was 2218 mIU/ml [> 15% decrease of ß-hCG (42.4%)]; therefore, she was discharged home for follow-up in the outpatient department. This report represents the treatment of left undisturbed tubal pregnancy with foetal cardiac activity using a two-dose MTX regimen.

Identification of physiological response functions to correct for fluctuations in resting-state fMRI related to heart rate and respiration.

Functional magnetic resonance imaging (fMRI) is widely viewed as the gold standard for studying brain function due to its high spatial resolution and non-invasive nature. However, it is well established that changes in breathing patterns and heart rate strongly influence the blood oxygen-level dependent (BOLD) fMRI signal and this, in turn, can have considerable effects on fMRI studies, particularly resting-state studies. The dynamic effects of physiological processes are often quantified by using convolution models along with simultaneously recorded physiological data. In this context, physiological response function (PRF) curves (cardiac and respiratory response functions), which are convolved with the corresponding physiological fluctuations, are commonly employed. While it has often been suggested that the PRF curves may be region- or subject-specific, it is still an open question whether this is the case. In the present study, we propose a novel framework for the robust estimation of PRF curves and use this framework to rigorously examine the implications of using population-, subject-, session- and scan-specific PRF curves. The proposed framework was tested on resting-state fMRI and physiological data from the Human Connectome Project. Our results suggest that PRF curves vary significantly across subjects and, to a lesser extent, across sessions from the same subject. These differences can be partly attributed to physiological variables such as the mean and variance of the heart rate during the scan. The proposed methodological framework can be used to obtain robust scan-specific PRF curves from data records with duration longer than 5 min, exhibiting significantly improved performance compared to previously defined canonical cardiac and respiration response functions. Besides removing physiological confounds from the BOLD signal, accurate modeling of subject- (or session-/scan-) specific PRF curves is of importance in studies that involve populations with altered vascular responses, such as aging subjects.

Real-Time Cardiac Beat Detection and Heart Rate Monitoring from Combined Seismocardiography and Gyrocardiography.

Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG-GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36-140 bpm. The correlation between the two measurements had r2 coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact.

Cardiac Measures of Cognitive Workload: A Meta-Analysis.

OBJECTIVE: We aimed to provide an assessment of the impact of workload manipulations on various cardiac measurements. We further sought to determine the most effective measurement approaches of cognitive workload as well as quantify the conditions under which these measures are most effective for interpretation. BACKGROUND: Cognitive workload affects human performance, particularly when load is relatively high (overload) or low (underload). Despite ongoing interest in assessing cognitive workload through cardiac measures, it is currently unclear which cardiac-based assessments best indicate cognitive workload. Although several quantitative studies and qualitative reviews have sought to provide guidance, no meta-analytic integration of cardiac assessment(s) of cognitive workload exists to date. METHOD: We used Morris and DeShon's meta-analytic procedures to quantify the changes in cardiac measures due to task load conditions. RESULTS: Sample-weighted Cohen's d values suggest that several metrics of cardiac activity demonstrate sensitivity in response to cognitive workload manipulations. Heart rate variability measures show sensitivity to task load, conditions of event rate, and task duration. Authors of future work should seek to quantify the utility of leveraging multiple metrics to understand workload. CONCLUSION: Results suggest that assessment of cognitive workload can be done using various cardiac activity indicators. Further, given the number of valid and reliable measures available, researchers and practitioners should base their selection of a psychophysiological measure on the experimental and practical concerns inherent to their task/protocol. APPLICATIONS: Findings bear implications for future assessment of cognitive workload within basic and applied settings. Future research should seek to validate conditions under which measurements are best interpreted, including but not limited to individual differences.

Heart rate and respiration influence on macroscopic blood and CSF flows.

Background Changes in blood volume in the intracranial arteries and the resulting oscillations of brain parenchyma have been presumed as main initiating factors of cerebrospinal fluid (CSF) pulsations. However, respiration has been recently supposed to influence CSF dynamics via thoracic pressure changes. Purpose To measure blood and CSF cervical flow and quantify the contribution of cardiac and respiratory cycles on the subsequent signal evolution. Material and Methods Sixteen volunteers were enrolled. All participant underwent two-dimensional fast field echo echo planar imaging (FFE-EPI). Regions of interest were placed on internal carotids, jugular veins, and rachidian canal to extract temporal profiles. Spectral analysis was performed to extract respiratory and cardiac frequencies. The contribution of respiration and cardiac activity was assessed to signal evolution by applying a multiple linear model. Results Mean respiratory frequency was 14.6 ± 3.9 cycles per min and mean heart rate was 66.8 ± 9 cycles per min. Cardiac contribution was higher than breathing for internal carotids, explaining 74.68% and 10.27% of the signal variance, respectively. For the jugular veins, respiratory component was higher than the cardiac one contributing 44.28% and 6.53% of the signal variance, respectively. For CSF, breathing and cardiac component contributed less than half of signal variance (12.61% and 23.23%, respectively). Conclusion Respiration and cardiac activity both influence fluid flow at the cervical level. Arterial inflow is driven by the cardiac pool whereas venous blood aspiration seems more due to thoracic pressure changes. CSF dynamics acts as a buffer between these two blood compartments.

Two-year outcome after recurrent first trimester miscarriages: prognostic value of the past obstetric history.

PURPOSE: Recurrent miscarriage (RM) is a stressful condition which gives rise to extensive diagnostic evaluation and is seen as a potentially curable maternal disease. Nevertheless, epidemiological data have shown that outcome is related to fertility. In addition to maternal age and number of preceding miscarriages, further markers derived from the past history may support counselling. METHODS: Observational trial comprising 228 couples who were referred between 1996 and 2003 for immunological evaluation at maternal ages 20-39 years after three or more spontaneously conceived primary first trimester miscarriages. They were interviewed in 2005, ongoing pregnancies were followed up until birth in 2006. Past obstetric history was correlated with 2 year cumulative pregnancy and delivery rates (CPR, CDR). RESULTS: CPR and CDR were 206/228 (90.4 %) and 174/228 (76.4 %). Duration of infertility was associated with lower CPR (up to 3/>3 years, p < 0.01), whereas age and number of preceding losses inversely correlated with CDR (<35 years/35-39 years, p < 0.002; 3/>3 miscarriages, p < 0.002). Detection of an embryonic heart beat in 2-3 of the first three miscarriages resulted in favourable outcome (CPR: p < 0.02, CDR: p < 0.002). Prognosis was excellent in younger fertile women after three miscarriages where vital signs had been detected; under less favourable conditions not only risks for further miscarriage, but also for secondary infertility were elevated. CONCLUSION: Secondary infertility is a feature of RM. Embryonic vital signs in preceding pregnancies are prognostic markers and should be regarded as a strong confounding factor in trials on therapeutic interventions. Prevention may be more appropriate than treatment.

[Electroimpedance Methods of Investigation of Cardiac Activity].

AIM: of the present work was assessment of possibility to use modern electroimpedace methods for the study of activity of the heart. Electroimpemdace methods of measurement for many years remained in the shadow of other diagnostic methods because of low accuracy in evaluation of various parameters. At present, there are technologies of measurement which allow to carry out electroimpedance investigations of cardiac activity dynamically and with acceptable accuracy. In this article, we present methods of electroimpedace measurements created in Institute of Biomedical Equipment of N.E. Bauman Technical University. These methods allow to assess dynamics of movement of ventricles of the heart, to evaluate volume parameters of cardiac activity and all temporal phases of activity of cardiac chambers. We also present data of studies on healthy volunteers and patients of cardiological profile. It has been shown that patients with atrial fibrillation have substantially increased duration of electrical and mechanical activity of atria and ventricles as well as lowed ejection fraction compared with other participants of experiments.

Right-nostril use during sniffing at arousing stimuli produces higher cardiac activity in jumper horses.

Lateralization in horses, Equus caballus, has been reported at both motor and sensory levels. Here we investigated left- and right-nostril use in 12 jumper horses freely sniffing different emotive stimuli. Results revealed that during sniffing at adrenaline and oestrus mare urine stimuli, horses showed a clear right-nostril bias while just a tendency in the use of the right nostril was observed during sniffing of other odours (food, cotton swab and repellent). Sniffing at adrenaline and urine odours was also accompanied by increasing cardiac activity and behavioural reactivity strengthening the role of the right hemisphere in the analysis of intense emotion and sexual behaviour.

Comprehensive Assessment of Graphene Oxide Nanoparticles: Effects on Liver Enzymes and Cardiovascular System in Animal Models and Skeletal Muscle Cells.

The growing interest in graphene oxide (GO) for different biomedical applications requires thoroughly examining its safety. Therefore, there is an urgent need for reliable data on how GO nanoparticles affect healthy cells and organs. In the current work, we adopted a comprehensive approach to assess the influence of GO and its polyethylene glycol-modified form (GO-PEG) under near-infrared (NIR) exposure on several biological aspects. We evaluated the contractility of isolated frog hearts, the activity of two rat liver enzymes-mitochondrial ATPase and diamine oxidase (DAO), and the production of reactive oxygen species (ROS) in C2C12 skeletal muscle cells following direct exposure to GO nanoparticles. The aim was to study the influence of GO nanoparticles at multiple levels-organ; cellular; and subcellular-to provide a broader understanding of their effects. Our data demonstrated that GO and GO-PEG negatively affect heart contractility in frogs, inducing stronger arrhythmic contractions. They increased ROS production in C2C12 myoblasts, whose effects diminished after NIR irradiation. Both nanoparticles in the rat liver significantly stimulated DAO activity, with amplification of this effect after NIR irradiation. GO did not uncouple intact rat liver mitochondria but caused a concentration-dependent decline in ATPase activity in freeze/thaw mitochondria. This multifaceted investigation provides crucial insights into GOs potential for diverse implications in biological systems.

Responses of zebra and quagga mussels to copper and tribytiltin exposure: Bioconcentration, metabolic and cardiac biomarkers.

One of the top ecological priorities is to find sensitive indicators for pollution monitoring. This study focuses on the bioconcentration and responses (condition index, survival, oxygen consumption, heart rates, and oxidative stress and neurotoxic effect biomarkers) of mussels from the Volga River basin, Dreissena polymorpha and Dreissena bugensis, to long-term exposure to toxic chemicals such as tributyltin (TBT, 25 and 100 ng/L) and copper (Cu, 100 and 1000 µg/L). We found that TBT was present in the tissues of zebra and quagga mussels in comparable amounts, whereas the bioconcentration factor of Cu varied depending on its concentration in water. Differences in responses between the two species were revealed. When exposed to high Cu concentrations or a Cu-TBT mixture, quagga mussels had a lower survival rate and a longer heart rate recovery time than zebra mussels. TBT treatment caused neurotoxicity (decreased acetylcholinesterase activity) and oxidative stress (increased levels of thiobarbituric acid reactive substances) in both species. TBT and Cu levels in mussel tissues correlated positively with the condition index, but correlated with the level of acetylcholinesterase in the mussel gills. The principal component analysis revealed three main components: the first consists of linear combinations of 14 variables reflecting TBT water pollution, TBT and Cu levels in mussel tissues, and biochemical indicators; the second includes Cu water concentration, cardiac tolerance, and mussel size; and the third combines weight, metabolic rate, and heart rates. Quagga mussels are less tolerable to contaminants than zebra mussels, so they may be used as a sensitive indicator.

Monitoring Resistance Training in Real Time with Wearable Technology: Current Applications and Future Directions.

Resistance training is an exercise modality that involves using weights or resistance to strengthen and tone muscles. It has become popular in recent years, with numerous people including it in their fitness routines to ameliorate their strength, muscle mass, and overall health. Still, resistance training can be complex, requiring careful planning and execution to avoid injury and achieve satisfactory results. Wearable technology has emerged as a promising tool for resistance training, as it allows monitoring and adjusting training programs in real time. Several wearable devices are currently available, such as smart watches, fitness trackers, and other sensors that can yield detailed physiological and biomechanical information. In resistance training research, this information can be used to assess the effectiveness of training programs and identify areas for improvement. Wearable technology has the potential to revolutionize resistance training research, providing new insights and opportunities for developing optimized training programs. This review examines the types of wearables commonly used in resistance training research, their applications in monitoring and optimizing training programs, and the potential limitations and challenges associated with their use. Finally, it discusses future research directions, including the development of advanced wearable technologies and the integration of artificial intelligence in resistance training research.

Role of initial cardiac activity assessed by point-of-care ultrasonography in predicting cardiac arrest outcomes: A prospective cohort study.

OBJECTIVES: This study was conducted to investigate the association between visible cardiac activity in point-of-care ultrasound (POCUS) and outcomes of cardiac arrest such as the return of spontaneous circulation (ROSC), survival to inpatient admission (SIA), and survival to hospital discharge (STHD). METHODS: This was a single-center, prospective cohort study conducted in the emergency department (ED). Adult (age >18 years) patients in cardiac arrest were included in the study. Exclusion criteria of the study were - traumatic arrest, out-of-hospital cardiac arrest resuscitated before ED admission, and patients presenting with initial shockable rhythm. Patients whose ultrasound images could not be obtained and whose resuscitation stopped following POCUS were also excluded from the study. POCUS examination was done after 2 min of initiation of cardiopulmonary resuscitation (CPR) and visible cardiac activity was defined as any visible movement of the myocardium, excluding movement of blood within cardiac chambers, or isolated valve movement. The duration of POCUS examinations was limited to 10 s. The association of initial cardiac activity in POCUS with the outcomes of cardiac arrest was investigated. RESULTS: Out of 140 patients screened, 84 patients were included in the study. Rates of ROSC, SIA, and STHD were found in 23 (27.4%), 9 (10.7%), and 2 (2.4%) patients, respectively. Only 15 out of 84 (17.9%) patients had cardiac activity on the initial POCUS examination. Cardiac activity was seen in 52.2% of patients with ROSC, which was significantly higher (P < 0.001) as compared with the no-ROSC group (4.9%). Unlike the above association, there was no difference in the incidence of initial cardiac activity in patient groups who got admitted (SIA) and discharged (STHD) versus those who died. In the multivariate regression analysis, the duration of CPR and initial cardiac activity significantly predicted the rate of ROSC, with an adjusted odds ratio of 0.93 (95% confidence interval [CI]: 0.86-0.99, P = 0.04) and 24.8 (95% CI: 3.17-89.41, P = 0.002), respectively. None of the variables predicted SIA and STHD. The positive likelihood ratio of cardiac activity for predicting ROSC, SIA, and STHD were 10.6, 2.1, and 2.9, respectively. CONCLUSION: Integration of POCUS in cardiac arrest resuscitation was shown to be helpful in terms of prognostic significance of the presence of initial cardiac activity in terms of ROSC.

The Evaluation of Remote Monitoring Technology Across Participants With Different Skin Tones.

BACKGROUND: Many research studies seek to improve vital sign monitoring to enhance the conditions under which doctors and caregivers track patients' health. Non-invasive and contactless monitoring has emerged as an optimal solution for this problem, with telemedicine, self-monitoring, and well-being tools being the next generation of technology in the biomedical field. However, there is worldwide concern about the general purpose and bias toward a certain demographic group of these techniques. In particular, skin tone and the accuracy of monitoring dark skin tone groups have been key questions among researchers, with the lack of results and studies contributing to this uncertainty. METHODS: This paper proposes a benchmark for remote monitoring solutions against a medical device across different skin tone people. Around 330 videos from 90 patients were analyzed, and heart rate (HR) and heart rate variability (HRV) were compared across different subgroups. The Fitzpatrick scale (1-6) was used to classify participants into three skin tone groups: 1 and 2, 3 and 4, and 5 and 6. RESULTS: The results showed that our proposed methodology could estimate heart rate with a mean absolute error of 3 bpm across all samples and subgroups. Moreover, for heart rate variability (HRV) metrics, we achieved the following results: in terms of mobility assistive equipment (MAE), the HRV-inter-beat interval (IBI) was 10 ms, the HRV-standard deviation of normal to normal heartbeats (SDNN) was 14 ms, and the HRV-root mean square of successive differences (RMSSD) between normal heartbeats was 22 ms. No significant performance decrease was found for any skin tone group, and there was no error trend toward a certain group. CONCLUSIONS: The study showed that our methodology meets acceptable agreement levels for the proposed metrics. Furthermore, the experiments showed that skin tone did not impact the results, which remained within the same range across all groups. Moreover, it enables the end users to understand their general well-being and improve their overall health.

Ear your heart: transcutaneous auricular vagus nerve stimulation on heart rate variability in healthy young participants.

Background: Transcutaneous auricular vagus nerve stimulation (taVNS) stimulating the auricular branch of the vagus nerve along a well-defined neuroanatomical pathway, has promising therapeutic efficacy. Potentially, taVNS can modulate autonomic responses. Specifically, taVNS can induce more consistent parasympathetic activation and may lead to increased heart rate variability (HRV). However, the effects of taVNS on HRV remain inconclusive. Here, we investigated changes in HRV due to brief alteration periods of parasympathetic-vagal cardiac activity produced by taVNS on the cymba as opposed to control administration via the helix. Materials and Methods: We compared the effect of 10 min of active stimulation (i.e., cymba conchae) to sham stimulation (i.e., helix) on peripheral cardiovascular response, in 28 healthy young adults. HRV was estimated in the time domain and frequency domain during the overall stimulation. Results: Although active-taVNS and sham-taVNS stimulation did not differ in subjective intensity ratings, the active stimulation of the cymba led to vagally mediated HRV increases in both the time and frequency domains. Differences were significant between active-taVNS and both sham-taVNS and resting conditions in the absence of stimulation for various HRV parameters, but not for the low-frequency index of HRV, where no differences were found between active-taVNS and sham-taVNS conditions. Conclusion: This work supports the hypothesis that taVNS reliably induces a rapid increase in HRV parameters when auricular stimulation is used to recruit fibers in the cymba compared to stimulation at another site. The results suggest that HRV can be used as a physiological indicator of autonomic tone in taVNS for research and potential therapeutic applications, in line with the established effects of invasive VNS. Knowledge of the physiological effect of taVNS short sessions in modulating cardiovagal processing is essential for enhancing its clinical use.