A mathematical model for electrical stimulation of a monolayer of cardiac cells

Broadly applicable methods for the detection of artefacts in electroencephalography acquired simultaneously with hemodynamic recordings

Electroencephalography (EEG) data, acquired simultaneously with magnetic resonance imaging (MRI), must be corrected for artefacts related to MR gradient switches (GS) and the cardioballistic (CB) effect. Canonical approaches require additional signal acquisition for artefact detection (e.g., MR volume onsets, ECG), without which the EEG data would be rendered uncleanable from these artefacts.•We present two broadly applicable methods for artefact detection based on peak detection combined with temporal constraints with respect to periodicity directly from the EEG data itself; no additional signals are required. We validated the performance of our methods versus the two canonical approaches for detection of GS/CB artefact, respectively, on 26 healthy human EEG-functional MRI resting-state datasets. Utilising various performance metrics, we found our methods to perform as well as - and sometimes better than - the canonical standard approaches. With as little as one EEG channel recording, our methods can be applied to detect GS/CB artefacts in EEG data acquired simultaneously with MRI in the absence of MR volume onsets and/or an ECG recording. The detected artefact onsets can then be fed into the standard artefact correction software.

A Machine Learning Approach for the Detection of QRS Complexes in Electrocardiogram (ECG) Using Discrete Wavelet Transform (DWT) Algorithm

This study describes a modified approach for the detection of cardiac abnormalities and QRS complexes using machine learning and support vector machine (SVM) classifiers. The suggested technique overtakes prevailing approaches in terms of both sensitivity and specificity, with 0.45 percent detection error rate for cardiac irregularities. Moreover, the vector machine classifiers validated the proposed method's superiority by accurately categorising four ECG beat types: normal, LBBBs, RBBBs, and Paced beat. The technique had 96.67 percent accuracy in MLP-BP and 98.39 percent accuracy in support of vector machine classifiers. The results imply that the SVM classifier can play an important role in the analysis of cardiac abnormalities. Furthermore, the SVM classifier also categorises ECG beats using DWT characteristics collected from ECG signals.

What are the effects of acute exercise and exercise training on cerebrovascular hemodynamics following stroke? A systematic review and meta-analysis

INTRODUCTION

Limited data exist regarding the effects of acute exercise and exercise training on cerebrovascular hemodynamic variables post-stroke.

PURPOSE

This systematic review and meta-analysis 1) examined the effects of acute exercise and exercise training on cerebrovascular hemodynamic variables reported in the stroke exercise literature; and 2) synthesized the peak middle cerebral artery blood velocity (MCAv) achieved during an acute bout of moderate-intensity exercise in individuals post-stroke.

METHODS

Six databases (MEDLINE, EMBASE, Web of Science, CINAHL, PsycINFO, AMED) were searched from inception to December 1^st 2021, for studies that examined the effect of acute exercise or exercise training on cerebrovascular hemodynamics in adults post-stroke. Two reviewers conducted title and abstract screening, full-text evaluation, data extraction, and quality appraisal. Random effects models were used in meta-analysis.

RESULTS

Nine studies, including 4 acute exercise (n=61) and 5 exercise training studies (n=193), were included. Meta-analyses were not statistically feasible for several cerebrovascular hemodynamic variables. Descriptive analysis reveals that exercise training may increase cerebral blood flow and cerebrovascular reactivity to carbon dioxide among individuals post-stroke. Meta-analysis of three acute exercise studies revealed no significant changes in MCAv during acute moderate intensity exercise (n=48 participants, mean difference = 5.2 cm/s, 95% CI [-0.6, 11.0], P=0.08) compared to resting MCAv values.

CONCLUSION

This review suggests that individuals post-stroke may have attenuated cerebrovascular hemodynamics as measured by the MCAv during acute moderate-intensity exercise. Higher quality research utilizing agreed upon hemodynamic variables are needed to synthesize the effects of exercise training on cerebrovascular hemodynamics post-stroke.

Muscle Thickness and Curvature Influence Atrial Conduction Velocities

Electroanatomical mapping is currently used to provide clinicians with information about the electrophysiological state of the heart and to guide interventions like ablation. These maps can be used to identify ectopic triggers of an arrhythmia such as atrial fibrillation (AF) or changes in the conduction velocity (CV) that have been associated with poor cell to cell coupling or fibrosis. Unfortunately, many factors are known to affect CV, including membrane excitability, pacing rate, wavefront curvature, and bath loading, making interpretation challenging. In this work, we show how endocardial conduction velocities are also affected by the geometrical factors of muscle thickness and wall curvature. Using an idealized three-dimensional strand, we show that transverse conductivities and boundary conditions can slow down or speed up signal propagation, depending on the curvature of the muscle tissue. In fact, a planar wavefront that is parallel to a straight line normal to the mid-surface does not remain normal to the mid-surface in a curved domain. We further demonstrate that the conclusions drawn from the idealized test case can be used to explain spatial changes in conduction velocities in a patient-specific reconstruction of the left atrial posterior wall. The simulations suggest that the widespread assumption of treating atrial muscle as a two-dimensional manifold for electrophysiological simulations will not accurately represent the endocardial conduction velocities in regions of the heart thicker than 0.5 mm with significant wall curvature.

Clustering-Constrained ICA for Ballistocardiogram Artifacts Removal in Simultaneous EEG-fMRI

Combination of electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) plays a potential role in neuroimaging due to its high spatial and temporal resolution. However, EEG is easily influenced by ballistocardiogram (BCG) artifacts and may cause false identification of the related EEG features, such as epileptic spikes. There are many related methods to remove them, however, they do not consider the time-varying features of BCG artifacts. In this paper, a novel method using clustering algorithm to catch the BCG artifacts' features and together with the constrained ICA (ccICA) is proposed to remove the BCG artifacts. We first applied this method to the simulated data, which was constructed by adding the BCG artifacts to the EEG signal obtained from the conventional environment. Then, our method was tested to demonstrate the effectiveness during EEG and fMRI experiments on 10 healthy subjects. In simulated data analysis, the value of error in signal amplitude (Er) computed by ccICA method was lower than those from other methods including AAS, OBS, and cICA (p < 0.005). In vivo data analysis, the Improvement of Normalized Power Spectrum (INPS) calculated by ccICA method in all electrodes was much higher than AAS, OBS, and cICA methods (p < 0.005). We also used other evaluation index (e.g., power analysis) to compare our method with other traditional methods. In conclusion, our novel method successfully and effectively removed BCG artifacts in both simulated and vivo EEG data tests, showing the potentials of removing artifacts in EEG-fMRI applications.

Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal

One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory.

Therapeutic ultrasound for glaucoma: clinical use of a low-frequency low-power ultrasound device for lowering intraocular pressure

BACKGROUND

This is a first-in-human study to determine the efficacy and tolerability of a new method of treating glaucoma using a low-power, low-frequency, focused therapeutic ultrasound for glaucoma (TUG) device designed to trigger an inflammatory reaction in the anterior chamber angle and trabecular meshwork to enhance outflow. The use of the device is anticipated for mild or moderate open-angle glaucoma as an enhancement to outflow.

METHODS

In a two-branch clinical trial, a total of 26 primary open-angle glaucoma patients underwent a procedure consisting of the external application of the TUG device. In branch 1, nine of these patients were naïve to pharmaceutical treatment or had been off of medication for over 6 months. In branch 2, 17 patients were treated after a medication washout period. All patients in the study were followed for 12 months.

RESULTS

In branch 1, there was a decrease in intraocular pressure averaging over 20% lasting at least a year in 74% of the eyes with non-normotensive open-angle glaucoma. In branch 2, an average of two visits while on medication provided the comparison intraocular pressure (IOP) to the effect of the TUG treatment after washout. It was seen that the intraocular pressure over the year post-treatment was equal to or better than the pharmaceutical control in close to 80% of measurements.

CONCLUSION

A novel device for lowering intraocular pressure is described with a potential for adding to our armamentarium for treating glaucoma. This is a small cohort study which indicates beneficial trends.

TRIAL REGISTRATION NUMBER

The study was a registered clinical trial, #ISRCTN50904302.

Automated diagnosis of autism: in search of a mathematical marker

Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-the-art review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEG-based diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder.

Toward online modeling for lesion visualization and monitoring in cardiac ablation therapy

Despite extensive efforts to enhance catheter navigation, limited research has been done to visualize and monitor the tissue lesions created during ablation in the attempt to provide feedback for effective therapy. We propose a technique to visualize the temperature distribution and extent of induced tissue injury via an image-based model that uses physiological tissue parameters and relies on heat transfer principles to characterize lesion progression in near real time. The model was evaluated both numerically and experimentally using ex vivo bovine muscle samples while emulating a clinically relevant ablation protocol. Results show agreement to within 5 degreeC between the model-predicted and experimentally measured end-ablation tissue temperatures, as well as comparable predicted and observed lesion characteristics. The model yields temperature and lesion updates in near real-time, thus providing reasonably accurate and sufficiently fast monitoring for effective therapy.

Role of caveolin-1 in thyroid phenotype, cell homeostasis, and hormone synthesis: in vivo study of caveolin-1 knockout mice

In human thyroid, caveolin-1 is localized at the apex of thyrocytes, but its role there remains unknown. Using immunohistochemistry, (127)I imaging, transmission electron microscopy, immunogold electron microscopy, and quantification of H(2)O(2), we found that in caveolin-1 knockout mice thyroid cell homeostasis was disrupted, with evidence of oxidative stress, cell damage, and apoptosis. An even more striking phenotype was the absence of thyroglobulin and iodine in one-half of the follicular lumina and their presence in the cytosol, suggesting that the iodide organification and binding to thyroglobulin were intracellular rather than at the apical membrane/extracellular colloid interface. The latter abnormality may be secondary to the observed mislocalization of the thyroid hormone synthesis machinery (dual oxidases, thyroperoxidase) in the cytosol. Nevertheless, the overall uptake of radioiodide, its organification, and secretion as thyroid hormones were comparable to those of wild-type mice, suggesting adequate compensation by the normal TSH retrocontrol. Accordingly, the levels of free thyroxine and TSH were normal. Only the levels of free triiodothyronine showed a slight decrease in caveolin-1 knockout mice. However, when TSH levels were increased through low-iodine chow and sodium perchlorate, the induced goiter was more prominent in caveolin-1 knockout mice. We conclude that caveolin-1 plays a role in proper thyroid hormone synthesis as well as in cell number homeostasis. Our study demonstrates for the first time a physiological function of caveolin-1 in the thyroid gland. Because the expression and subcellular localization of caveolin-1 were similar between normal human and murine thyroids, our findings in caveolin-1 knockout mice may have direct relevance to the human counterpart.