Feasibility Analysis of ECG-Based pH Estimation for Asphyxia Detection in Neonates.

Birth asphyxia is a potential cause of death that is also associated with acute and chronic morbidities. The traditional and immediate approach for monitoring birth asphyxia (i.e., arterial blood gas analysis) is highly invasive and intermittent. Additionally, alternative noninvasive approaches such as pulse oximeters can be problematic, due to the possibility of false and erroneous measurements. Therefore, further research is needed to explore alternative noninvasive and accurate monitoring methods for asphyxiated neonates. This study aims to investigate the prominent ECG features based on pH estimation that could potentially be used to explore the noninvasive, accurate, and continuous monitoring of asphyxiated neonates. The dataset used contained 274 segments of ECG and pH values recorded simultaneously. After preprocessing the data, principal component analysis and the Pan-Tompkins algorithm were used for each segment to determine the most significant ECG cycle and to compute the ECG features. Descriptive statistics were performed to describe the main properties of the processed dataset. A Kruskal-Wallis nonparametric test was then used to analyze differences between the asphyxiated and non-asphyxiated groups. Finally, a Dunn-Sidák post hoc test was used for individual comparison among the mean ranks of all groups. The findings of this study showed that ECG features (T/QRS, T Amplitude, Tslope, Tslope/T, Tslope/|T|, HR, QT, and QTc) based on pH estimation differed significantly (p < 0.05) in asphyxiated neonates. All these key ECG features were also found to be significantly different between the two groups.

Implantable Pressure-Sensing Devices for Monitoring Abdominal Aortic Aneurysms in Post-Endovascular Aneurysm Repair.

Over the past two decades, there has been extensive research into surveillance methods for the post-endovascular repair of abdominal aortic aneurysms, highlighting the importance of these technologies in supplementing or even replacing conventional image-screening modalities. This review aims to provide an overview of the current status of alternative surveillance solutions for endovascular aneurysm repair, while also identifying potential aneurysm features that could be used to develop novel monitoring technologies. It offers a comprehensive review of these recent clinical advances, comparing new and standard clinical practices. After introducing the clinical understanding of abdominal aortic aneurysms and exploring current treatment procedures, the paper discusses the current surveillance methods for endovascular repair, contrasting them with recent pressure-sensing technologies. The literature on three commercial pressure-sensing devices for post-endovascular repair surveillance is analyzed. Various pre-clinical and clinical studies assessing the safety and efficacy of these devices are reviewed, providing a comparative summary of their outcomes. The review of the results from pre-clinical and clinical studies suggests a consistent trend of decreased blood pressure in the excluded aneurysm sac post-repair. However, despite successful pressure readings from the aneurysm sac, no strong link has been established to translate these measurements into the presence or absence of endoleaks. Furthermore, the results do not allow for a conclusive determination of ongoing aneurysm sac growth. Consequently, a strong clinical need persists for monitoring endoleaks and aneurysm growth following endovascular repair.

Design and Characterisation of a Read-Out System for Wireless Monitoring of a Novel Implantable Sensor for Abdominal Aortic Aneurysm Monitoring.

Abdominal aortic aneurysm (AAA) is a dilation of the aorta artery larger than its normal diameter (>3 cm). Endovascular aneurysm repair (EVAR) is a minimally invasive treatment option that involves the placement of a graft in the aneurysmal portion of the aorta artery. This treatment requires multiple follow-ups with medical imaging, which is expensive, time-consuming, and resource-demanding for healthcare systems. An alternative solution is the use of wireless implantable sensors (WIMSs) to monitor the growth of the aneurysm. A WIMS capable of monitoring aneurysm size longitudinally could serve as an alternative monitoring approach for post-EVAR patients. This study has developed and characterised a three-coil inductive read-out system to detect variations in the resonance frequency of the novel Z-shaped WIMS implanted within the AAA sac. Specifically, the spacing between the transmitter and the repeater inductors was optimised to maximise the detection of the sensor by the transmitter inductor. Moreover, an experimental evaluation was also performed for different orientations of the transmitter coil with reference to the WIMS. Finally, the FDA-approved material nitinol was used to develop the WIMS, the transmitter, and repeater inductors as a proof of concept for further studies. The findings of the characterisation from the air medium suggest that the read-out system can detect the WIMS up to 5 cm, regardless of the orientation of the Z-shape WIMS, with the detection range increasing as the orientation approaches 0°. This study provides sufficient evidence that the proposed WIMS and the read-out system can be used for AAA expansion over time.

A Predictive and an Optimization Mathematical Model for Device Design in Cardiac Pulsed Field Ablation Using Design of Experiments.

Cardiac catheter ablation (CCA) is a common method used to correct cardiac arrhythmia. Pulsed Field Ablation (PFA) is a recently-adapted CCA technology whose ablation is dependent on electrode and waveform parameters (factors). In this work, the use of the Design of Experiments (DoE) methodology is investigated for the design and optimization of a PFA device. The effects of the four factors (input voltage, electrode spacing, electrode width, and on-time) and their interactions are analyzed. An empirical model is formed to predict and optimize the ablation size responses. Based on the ranges tested, the significant factors were the input voltage, the electrode spacing, and the on time, which is in line with the literature. Two-factor interactions were found to be significant and need to be considered in the model. The resulting empirical model was found to predict ablation sizes with less than 2.1% error in the measured area and was used for optimization. The findings and the strong predictive model developed highlight that the DoE approach can be used to help determine PFA device design, to optimize for certain ablation zone sizes, and to help inform device design to tackle specific cardiac arrhythmias.

In Vitro Models for Improved Therapeutic Interventions in Atrial Fibrillation.

Atrial fibrillation is the most common type of cardiac arrhythmias in humans, mostly caused by hyper excitation of specific areas in the atrium resulting in dyssynchronous atrial contractions, leading to severe consequences such as heart failure and stroke. Current therapeutics aim to target this condition through both pharmacological and non-pharmacological approaches. To test and validate any of these treatments, an appropriate preclinical model must be carefully chosen to refine and optimise the therapy features to correctly reverse this condition. A broad range of preclinical models have been developed over the years, with specific features and advantages to closely mimic the pathophysiology of atrial fibrillation. In this review, currently available models are described, from traditional animal models and in vitro cell cultures to state-of-the-art organoids and organs-on-a-chip. The advantages, applications and limitations of each model are discussed, providing the information to select the appropriate model for each research application.

Probe Contact Force Monitoring during Conductivity Measurements of the Left Atrial Appendage to Support the Design of Novel Diagnostic and Therapeutic Procedures.

The electrical properties of many biological tissues are freely available from the INRC and the IT'IS databases. However, particularly in lower frequency ranges, few studies have investigated the optimal measurement protocol or the key confounders that need to be controlled, monitored, and reported. However, preliminary work suggests that the contact force of the measurement probe on the tissue sample can affect the measurements. The aim of this paper is to investigate the conductivity change due to the probe contact force in detail. Twenty ex vivo bovine heart samples are used, and conductivity measurements are taken in the Left Atrial Appendage, a common target for medical device developments. The conductivity measurements reported in this work (between 0.14 S/m and 0.24 S/m) align with the literature. The average conductivity is observed to change by -21% as the contact force increases from 2 N to 10 N. In contrast, in conditions where the fluid concentration in the measurement area is expected to be lower, very small changes are observed (less than 2.5%). These results suggest that the LAA conductivity is affected by the contact force due to the fluid concentration in the tissue. This work suggests that contact force should be controlled for in all future experiments.

Electroporation Parameters for Human Cardiomyocyte Ablation In Vitro.

Cardiac ablation with irreversible electroporation (IRE) is quickly being established as a modality of choice for atrial fibrillation treatment. While it has not yet been optimised, IRE has the potential to significantly limit collateral damage and improve cell-specific targeting associated with other energy sources. However, more tissue and cell-specific evidence is required to demonstrate the selective threshold parameters for human cells. The aim here is to determine the optimal ablation threshold parameters related to lesion size for human cardiomyocytes in 2D culture. Conventional biphasic pulses of different field strengths and on-times were delivered in a monolayer culture system of human AC16 cardiomyocytes. The dynamics of cell death and lesion dimensions were examined at different time points. Human cardiomyocytes are susceptible to significant electroporation and cell death at a field strength of 750 V/cm or higher with 100 µs pulses. Increasing the IRE on-time from 3 ms to 60 ms reduces the effective field threshold to 250 V/cm. Using very short pulses of 2 µs and 5 µs also causes significant cell death, but only at fields higher than 1000 V/cm. A longer on-time results in more cell death and induced greater lesion area in 2D models. In addition, different forms of cell death are predicted based on the evolution of cell death over time. This study presents important findings on the ability of different IRE parameters to induce human cardiomyocyte cell death. Lesion size can be tuned by appropriate choice of IRE parameters and cardiomyocytes display an upregulation of delayed cell death 24 h after electroporation, which is an important consideration for clinical practice.

Gamma Band Light Stimulation in Human Case Studies: Groundwork for Potential Alzheimer's Disease Treatment.

BACKGROUND: It is known that proteins associated with Alzheimer's disease (AD) pathogenesis are significantly reduced by 40 Hz entrainment in mice. If this were to translate to humans, verifying that such a light stimulus can induce a 40 Hz entrainment response in humans and harnessing insights from these case studies could be one step in the development of a multisensory device to prevent and treat AD. OBJECTIVE: Verify the inducement of a 40 Hz response in the human brain by a 40 Hz light stimulus and obtain insights that could potentially aid in the development of a multisensory device for the prevention and treatment of AD. METHODS: Electroencephalographic brain activity was recorded simultaneously with application of stimulus at different frequencies and intensities. Power spectral densities were analyzed. RESULTS: Entrainment to visual stimuli occurred with the largest response at 40 Hz. The high intensity 40 Hz stimulus caused widespread entrainment. The number of electrodes demonstrating entrainment increased with increasing light intensity. Largest amplitudes for the high intensity 40 Hz stimulus were consistently found at the primary visual cortex. There was a harmonic effect at double the frequency for the 40 Hz stimulus. An eyes-open protocol caused more entrainment than an eyes-closed protocol. CONCLUSION: It was possible to induce widespread entrainment using a 40 Hz light stimulus in this sample cohort. Insights gleaned from these case studies could potentially aid in the development of a multisensory medical device to prevent and treat AD.

Detection of Vesicoureteral Reflux Using Electrical Impedance Tomography.

OBJECTIVE: The purpose of this study is to detect vesicoureteral reflux (VUR) noninvasively using an electrical impedance tomography (EIT). VUR is characterized by the backflow of urine from the bladder to the kidneys. METHODS: Using porcine models, small quantities of a solution mimicking the electrical properties of urine were infused into each ureter. EIT measurements were taken before, during and after the infusion using electrodes positioned around the abdomen. The collected data from 116 experiments were then processed and time-difference images reconstructed. Objective VUR detection was determined through statistical analysis of the mean change in the voltage signals and EIT image pixel intensities. RESULTS: Unilateral VUR was successfully detected in 94.83% of all mean voltage signals and in over 98.28% of the reconstructed images. The images showed strong visual contrast between the region of interest and the background. CONCLUSION: In animal models, EIT has the capability to detect reflux in the kidneys with high accuracy. The results show promise for EIT to be used for screening of VUR in children. SIGNIFICANCE: VUR is the most common congenital urinary tract abnormality in children. The condition predisposes children to urinary tract infections and kidney damage. The current gold standard diagnostic test, a voiding cystourethrogram, is invasive and uses ionizing radiation; therefore, there is a need for new tools for identifying VUR in children. This study presents a noninvasive method to detect VUR in animal models, illustrating the potential for EIT as a screening tool in clinical scenarios.

Image-based classification of bladder state using electrical impedance tomography.

OBJECTIVE: In this study, we examine the potential of using machine learning classification to determine the bladder state ('not full', 'full') with electrical impedance tomography (EIT) images of the pelvic region. Accurate classification of these states would enable urinary incontinence (UI) monitoring to alert the patient, before involuntary voiding occurs, in a low-cost and discrete manner. APPROACH: Using both numerical and experimental data, we form datasets that contain diverse observations with varying clinical parameters such as bladder volume, urine conductivity, and the reference used for time-difference imaging. We then classify the bladder state using both pixel-wise and feature extraction-based classification techniques. We employ principal component analysis, wavelets, and image segmentation to help create features. MAIN RESULTS: The performance was compared across several classifier algorithms. The minimum accuracy was 77.50%. The highest accuracy observed was 100%, and was found by combining principal component analysis and the Gaussian radial based function kernel support vector machine. This combination also offered the best trade-off between classification performance and the costs of training time and memory space. The biggest challenge in bladder state classification is classifying volumes near the separation volume of not full and full, in which choosing the most suitable classifier combination can minimize this error. SIGNIFICANCE: We performed the first machine learning classification of bladder EIT images, achieving high classification accuracies with both numerical and experimental data. This work highlights the potential of using image-based machine learning with an EIT device to support bladder monitoring for those suffering from UI.

Supervised Learning Classifiers for Electrical Impedance-based Bladder State Detection.

Urinary Incontinence affects over 200 million people worldwide, severely impacting the quality of life of individuals. Bladder state detection technology has the potential to improve the lives of people with urinary incontinence by alerting the user before voiding occurs. To this end, the objective of this study is to investigate the feasibility of using supervised machine learning classifiers to determine the bladder state of 'full' or 'not full' from electrical impedance measurements. Electrical impedance data was obtained from computational models and a realistic experimental pelvic phantom. Multiple datasets with increasing complexity were formed for varying noise levels in simulation. 10-Fold testing was performed on each dataset to classify 'full' and 'not full' bladder states, including phantom measurement data. Support vector machines and k-Nearest-Neighbours classifiers were compared in terms of accuracy, sensitivity, and specificity. The minimum and maximum accuracies across all datasets were 73.16% and 100%, respectively. Factors that contributed most to misclassification were the noise level and bladder volumes near the threshold of 'full' or 'not full'. This paper represents the first study to use machine learning for bladder state detection with electrical impedance measurements. The results show promise for impedance-based bladder state detection to support those living with urinary incontinence.

A realistic pelvic phantom for electrical impedance measurement.

OBJECTIVE: To design and fabricate an anatomically and conductively accurate phantom for electrical impedance studies of non-invasive bladder volume monitoring. APPROACH: A modular pelvic phantom was designed and fabricated, consisting of a mechanically and conductively stable boundary wall, a background medium, and bladder phantoms. The wall and bladders are made of conductive polyurethane. The background material is an ultrasound gel-based mixture, with conductivity matched to a weighted average of the pelvic cavity organs, bone, muscle and fat. The phantom boundary is developed using a computer tomography model of a male human pelvis. The bladder phantoms were designed to correlate with human bladder dimensions. Electrical impedance measurements of the phantom were recorded, and images produced using six different bladder phantoms and a realistic finite element model. MAIN RESULTS: Five different bladder volumes were successfully imaged using an empty bladder as a reference. The average conductivity index from the reconstructed images showed a strong positive correlation with the bladder phantom volumes. SIGNIFICANCE: A conductively and anatomically accurate pelvic phantom was developed for non-invasive bladder volume monitoring using electrical impedance measurements. Several bladders were designed to correlate with actual human bladder volumes, allowing for accurate volume estimation. The conductivity of the phantom is accurate over 50-250 kHz. This phantom can allow changeable electrode location, contact and size; multi-layer electrodes configurations; increased complexity by addition of other organ or bone phantoms; and electrode movement and deformation. Overall, the pelvic phantom enables greater scope for experimentation and system refinement as a precursor to in-man clinical studies.