A Novel ECG Denoising Scheme Using the Ensemble Kalman Filter.

Monitoring of electrocardiogram (ECG) provides vital information as well as any cardiovascular anomalies. Recent advances in the technology of wearable electronics have enabled compact devices to acquire personal physiological signals in the home setting; however, signals are usually contaminated with high level noise. Thus, an efficient ECG filtering scheme is a dire need. In this paper, a novel method using Ensemble Kalman Filter (EnKF) is developed for denoising ECG signals. We also intensively explore various filtering algorithms, including Savitzky-Golay (SG) filter, Ensemble Empirical mode decomposition (EEMD), Normalized Least-Mean-Square (NLMS), Recursive least squares (RLS) filter, Total variation denoising (TVD), Wavelet and extended Kalman filter (EKF) for comparison. Data from the MIT-BIH Noise Stress Test database were used. The proposed methodology shows the average signal to noise ratio (SNR) of 10.96, the Percentage Root Difference of 150.45, and the correlation coefficient of 0.959 from the modified MIT-BIH database with added motion artifacts.

Microelectrode array membranes to simultaneously assess cardiac and neurological signals of xenopus laevis under chemical exposures and environmental changes.

Simultaneous monitoring of electrocardiogram (ECG) and electroencephalogram (EEG) in studied animal models requires innovative engineering techniques that can capture minute physiological changes. However, this is often administered with a bulky and/or invasive system that may cause discomfort to animals and signal distortions. Here, we develop an integrated bioelectronic sensing system to provide simultaneous recordings of ECG and EEG in real-time for Xenopus laevis. The microelectrode array (MEA) membrane and the distinct anatomy of Xenopus offer noninvasive multi-modal electrophysiological monitoring with favorable spatial resolution. The system was validated under different environmental conditions, including drug exposure and temperature changes. Under the exposure of Pentylenetetrazol (PTZ), an epilepsy-inducing drug, clear ECG and EEG alterations, including frequent ictal and interictal EEG events, 30 dB average EEG amplitude elevations, abnormal ECG morphology, and heart rate changes, were observed. Furthermore, the ECG and EEG were monitored and analyzed under different temperatures. A decrease in relative power of delta band was observed when cold environment was brought about, in contrast to an increase in relative power of other higher frequency bands while the ECG remained stable. Overall, the real-time electrophysiology monitoring system using the Xenopus model holds potential for many applications in drug screening and remote environmental monitoring.

Fetal Electrocardiogram Extraction from the Mother's Abdominal Signal Using the Ensemble Kalman Filter.

Fetal electrocardiogram (fECG) assessment is essential throughout pregnancy to monitor the wellbeing and development of the fetus, and to possibly diagnose potential congenital heart defects. Due to the high noise incorporated in the abdominal ECG (aECG) signals, the extraction of fECG has been challenging. And it is even a lot more difficult for fECG extraction if only one channel of aECG is provided, i.e., in a compact patch device. In this paper, we propose a novel algorithm based on the Ensemble Kalman filter (EnKF) for non-invasive fECG extraction from a single-channel aECG signal. To assess the performance of the proposed algorithm, we used our own clinical data, obtained from a pilot study with 10 subjects each of 20 min recording, and data from the PhysioNet 2013 Challenge bank with labeled QRS complex annotations. The proposed methodology shows the average positive predictive value (PPV) of 97.59%, sensitivity (SE) of 96.91%, and F1-score of 97.25% from the PhysioNet 2013 Challenge bank. Our results also indicate that the proposed algorithm is reliable and effective, and it outperforms the recently proposed extended Kalman filter (EKF) based algorithm.

A Low-Cost, 3D-Printed Biosensor for Rapid Detection of Escherichia coli.

Detection of bacterial pathogens is significant in the fields of food safety, medicine, and public health, just to name a few. If bacterial pathogens are not properly identified and treated promptly, they can lead to morbidity and mortality, also possibly contribute to antimicrobial resistance. Current bacterial detection methodologies rely solely on laboratory-based techniques, which are limited by long turnaround detection times, expensive costs, and risks of inadequate accuracy; also, the work requires trained specialists. Here, we describe a cost-effective and portable 3D-printed electrochemical biosensor that facilitates rapid detection of certain Escherichia coli (E. coli) strains (DH5α, BL21, TOP10, and JM109) within 15 min using 500 µL of sample, and costs only USD 2.50 per test. The sensor displayed an excellent limit of detection (LOD) of 53 cfu, limit of quantification (LOQ) of 270 cfu, and showed cross-reactivity with strains BL21 and JM109 due to shared epitopes. This advantageous diagnostic device is a strong candidate for frequent testing at point of care; it also has application in various fields and industries where pathogen detection is of interest.

Lullaby: A Novel Algorithm to Extract Fetal QRS in Real Time Using Periodic Trend Feature.

Fetal heart rate (fHR) is an important indicator for monitoring of fetal cardiac health and development. The widely-used method based on ultrasound, however, is not continuous and often requires an expert to perform; thus, it is mostly used in clinics during checkups. The advances in wearable technology have paved the way for home assessment of fHR via the extraction of the mother's abdominal electrocardiogram (ECG) acquired by novel patches. Several methods have been developed for such; however, the computation is either too slow for real-time monitoring or too heavy to be performed in a wearable. In this work, we develop and validate the Lullaby algorithm - a novel method for fetal QRS extraction from aECG. The results showed that Lullaby is almost 7 times faster than existing methods with a better F1-score of 0.815, holding promise to transform perinatal monitoring.

A novel wireless ECG system for prolonged monitoring of multiple zebrafish for heart disease and drug screening studies.

Zebrafish and their mutant lines have been extensively used in cardiovascular studies. In the current study, the novel system, Zebra II, is presented for prolonged electrocardiogram (ECG) acquisition and analysis for multiple zebrafish within controllable working environments. The Zebra II is composed of a perfusion system, apparatuses, sensors, and an in-house electronic system. First, the Zebra II is validated in comparison with a benchmark system, namely iWORX, through various experiments. The validation displayed comparable results in terms of data quality and ECG changes in response to drug treatment. The effects of anesthetic drugs and temperature variation on zebrafish ECG were subsequently investigated in experiments that need real-time data assessment. The Zebra II's capability of continuous anesthetic administration enabled prolonged ECG acquisition up to 1 h compared to that of 5 min in existing systems. The novel, cloud-based, automated analysis with data obtained from four fish further provided a useful solution for combinatorial experiments and helped save significant time and effort. The system showed robust ECG acquisition and analytics for various applications including arrhythmia in sodium induced sinus arrest, temperature-induced heart rate variation, and drug-induced arrhythmia in Tg(SCN5A-D1275N) mutant and wildtype fish. The multiple channel acquisition also enabled the implementation of randomized controlled trials on zebrafish models. The developed ECG system holds promise and solves current drawbacks in order to greatly accelerate drug screening applications and other cardiovascular studies using zebrafish.

Development of a Home-based Fetal Electrocardiogram (ECG) Monitoring System.

We develop a novel wearable fetal electrocardiogram (fECG) monitoring system consisting of an abdominal patch that communicates with a smart device. The system has two main components: the fetal patch and the monitoring app. The fetal patch has electronics and recording electrodes fabricated on a hybrid flexible-rigid platform while the Android app is developed for a wide range of applications. The patch collects the abdominal ECG (aECG) signals that are sent to the smart device app via secure Bluetooth Low Energy (BLE) communication. The app software connects to a cloud server where processing and extraction algorithms are executed for real-time fECG extraction and fetal heartrate (fHR) calculation from the collected raw data. We have validated the algorithms and real-time data recordings on pregnant subjects yielding promising results. Our system has the potential to transform the currently used fetal monitoring system to an effective distanced and telematernity care.

Deep learning-based framework for cardiac function assessment in embryonic zebrafish from heart beating videos.

Zebrafish is a powerful and widely-used model system for a host of biological investigations, including cardiovascular studies and genetic screening. Zebrafish are readily assessable during developmental stages; however, the current methods for quantifying and monitoring cardiac functions mainly involve tedious manual work and inconsistent estimations. In this paper, we developed and validated a Zebrafish Automatic Cardiovascular Assessment Framework (ZACAF) based on a U-net deep learning model for automated assessment of cardiovascular indices, such as ejection fraction (EF) and fractional shortening (FS) from microscopic videos of wildtype and cardiomyopathy mutant zebrafish embryos. Our approach yielded favorable performance with accuracy above 90% compared with manual processing. We used only black and white regular microscopic recordings with frame rates of 5-20 frames per second (fps); thus, the framework could be widely applicable with any laboratory resources and infrastructure. Most importantly, the automatic feature holds promise to enable efficient, consistent, and reliable processing and analysis capacity for large amounts of videos, which can be generated by diverse collaborating teams.

A Fluidics-Based Biosensor to Detect and Characterize Inhibition Patterns of Organophosphate to Acetylcholinesterase in Food Materials.

A chip-based electrochemical biosensor is developed herein for the detection of organophosphate (OP) in food materials. The principle of the sensing platform is based on the inhibition of dimethoate (DMT), a typical OP that specifically inhibits acetylcholinesterase (AChE) activity. Carbon nanotube-modified gold electrodes functionalized with polydiallyldimethylammonium chloride (PDDA) and oxidized nanocellulose (NC) were investigated for the sensing of OP, yielding high sensitivity. Compared with noncovalent adsorption and deposition in bovine serum albumin, bioconjugation with lysine side chain activation allowed the enzyme to be stable over three weeks at room temperature. The total amount of AChE was quantified, whose activity inhibition was highly linear with respect to DMT concentration. Increased incubation times and/or DMT concentration decreased current flow. The composite electrode showed a sensitivity 4.8-times higher than that of the bare gold electrode. The biosensor was challenged with organophosphate-spiked food samples and showed a limit of detection (LOD) of DMT at 4.1 nM, with a limit of quantification (LOQ) at 12.6 nM, in the linear range of 10 nM to 1000 nM. Such performance infers significant potential for the use of this system in the detection of organophosphates in real samples.

Continuous Electrocardiogram Monitoring in Zebrafish with Prolonged Mild Anesthesia.

The zebrafish model has been demonstrated as an ideal vertebrate model system for a diverse range of biological studies. Along with conventional approaches, monitoring and analysis of zebrafish electrocardiogram (ECG) have been utilized for cardio-physiological screening and elucidation. ECG monitoring has been carried out with fish treated with anesthetic drugs, rendering the short period of time in recording the signals (<5 min). In this work, a prolonged sedation system for continuous ECG monitoring of multiple zebrafish was proposed and developed. We built a circulation system to provide prolonged mild anesthesia which allows more consistent and intrinsic ECG measurement. The use of prolonged anesthesia helped reduce the concentration of the anesthetic drug (MS222 or Tricaine) from 200 mg/L to 100 mg/L and even lower; thus, maintaining the integrity of intrinsic ECG. Moreover, heartrate variation during recording was investigated, showing minute changes (±3.2 beats per minute - BPM). The development of this prolonged ECG monitoring system would open the possibility of long-term monitoring for studies such as drug screening and forward genetic screening.

Investigation of Methods to Extract Fetal Electrocardiogram from the Mother's Abdominal Signal in Practical Scenarios.

Monitoring of fetal electrocardiogram (fECG) would provide useful information about fetal wellbeing as well as any abnormal development during pregnancy. Recent advances in flexible electronics and wearable technologies have enabled compact devices to acquire personal physiological signals in the home setting, including those of expectant mothers. However, the high noise level in the daily life renders long-entrenched challenges to extract fECG from the combined fetal/maternal ECG signal recorded in the abdominal area of the mother. Thus, an efficient fECG extraction scheme is a dire need. In this work, we intensively explored various extraction algorithms, including template subtraction (TS), independent component analysis (ICA), and extended Kalman filter (EKF) using the data from the PhysioNet 2013 Challenge. Furthermore, the modified data with Gaussian and motion noise added, mimicking a practical scenario, were utilized to examine the performance of algorithms. Finally, we combined different algorithms together, yielding promising results, with the best performance in the F1 score of 92.61% achieved by an algorithm combining ICA and TS. With the data modified by adding different types of noise, the combination of ICA-TS-ICA showed the highest F1 score of 85.4%. It should be noted that these combined approaches required higher computational complexity, including execution time and allocated memory compared with other methods. Owing to comprehensive examination through various evaluation metrics in different extraction algorithms, this study provides insights into the implementation and operation of state-of-the-art fetal and maternal monitoring systems in the era of mobile health.

Biomimetic surgical mesh to replace fascia with tunable force-displacement.

Here we mimic the mechanical properties of native fascia to design surgical mesh for fascia replacement. Despite the widespread acceptance of synthetic materials as tissue scaffolds for pelvic floor disorders, mechanical property mismatch between mesh and adjacent native tissue drives fibrosis and erosion, leading the FDA to remove several surgical meshes from the market. However, autologous tissue does not induce either fibrosis or adjacent tissue erosion, suggesting the potential for biomimetic surgical mesh. In this study, we determined the design rules for mesh that mimics native fascia by mathematically modeling multi-component polymer networks, composed of elastin-like and collagen-like fibers, using a spring-network model. To validate the model, we measured the stress-strain curves of native bovine and nonhuman primate (Macaca mulatta) abdominal fascia in both toe and linear regions. We find that the stiffer collagen-like fibers must remain limp until the elastin-like fibers extend to the initial length of spanning collagen-like fibers under uniaxial tension. Comparing model results to experiment determines the product of fiber volume fraction and elastic modulus, a critical design parameter. Dual fiber mesh with mechanical properties that mimic fascia are feasible. These results have broad application to a wide range of soft tissue replacements including ~200,000 surgeries/year for pelvic floor disorders, because standard-of-care mesh contain only stiffer polymers that behave more like collagen than native tissue.

Designing pre-tensioned core-shell fibers to treat pelvic floor disorders.

Here we relate support provided to the pelvic floor by composite fibers having pre-tensioned cores secured by thin shells to tunable fiber properties. Surgical treatment of pelvic floor disorders including stress urinary incontinence and pelvic organ prolapse often inserts polymeric mesh to support pelvic fascia. However, achieving optimal levels of mesh tension and organ lift in minimally invasive surgeries remains challenging. Fibers with pre-tensioned cores and biodegradable shells have the potential to overcome this challenge by allowing reconstructive surgeons to "dial in" specific amounts of support without over tensioning mesh slings, which may lead to soft tissue erosion and voiding dysfunction. Consequently, this study quantifies the relationship between fiber dimensions and properties with the lift these fibers (once integrated into mesh) can provide to pelvic organs. Our linear elastic model quantifies the minimum and maximum amount of pre-tensioning allowed from tissue lift and core-shell delamination considerations, respectively. The model indicates that the elastic modulus of the biodegradable shell polymer should be orders of magnitude larger than that of the core polymer and be at least 10% of the core radius to preserve tension within the core that subsequently translates into tissue support.

Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges.

Mobile electroencephalography (mobile EEG) represents a next-generation neuroscientific technology - to study real-time brain activity - that is relatively inexpensive, non-invasive and portable. Mobile EEG leverages state-of-the-art hardware alongside established advantages of traditional EEG and recent advances in signal processing. In this review, we propose that mobile EEG could open unprecedented possibilities for studying neurodevelopmental disorders. We first present a brief overview of recent developments in mobile EEG technologies, emphasising the proliferation of studies in several neuroscientific domains. As these developments have yet to be exploited by neurodevelopmentalists, we then identify three research opportunities: 1) increase in the ease and flexibility of brain data acquisition in neurodevelopmental populations; 2) integration into powerful developmentally-informative research designs; 3) development of innovative non-stationary EEG-based paradigms. Critically, we address key challenges that should be considered to fully realise the potential of mobile EEG for neurodevelopmental research and for understanding developmental psychopathology more broadly, and suggest future research directions.

Home-based mobile fetal/maternal electrocardiogram acquisition and extraction with cloud assistance.

Electrocardiogram (ECG) monitoring of the fetus during pregnancy, before and during labor, can provide crucial information for the assessment of fetal well-being and development, as well as labor progress. An out-of-clinics fetal ECG monitoring system may pave the way for instant diagnosis, suggesting immediate intervention, which could help reduce the fetal mortality rate. In this paper, we present an unobtrusive fetal maternal ECG monitoring system which can operate in the home setting. The acquisition of the mother's abdominal ECG is done using the non-contact electrode approach. The extraction of the fetal ECG from the combined fetal/maternal ECG signal is investigated using both Fast Independent Component Analysis (FastICA) and RobustICA algorithms. An accelerometer is integrated for motion artifact detection which would help reduce interferences due to movement. The device also is connected to a cloud server, allowing doctors to access the data in real time.

Pilot Study of the Mirabilis System Prototype for Rapid Noninvasive Uterine Myoma Treatment Using an Ultrasound-Guided Volumetric Shell Ablation Technique.

STUDY OBJECTIVE: The primary objective of this pilot study was to evaluate the safety and acute tissue ablation efficacy of a transabdominal high-intensity focused ultrasound (HIFU) prototype device that uses ultrasound imaging guidance for rapid noninvasive ablation of uterine myomas. The secondary objective was to assess preliminary myoma-related symptom improvement and myoma volume reduction at 3 to 6 months post-treatment in subsets of patients. DESIGN: Multicenter prospective single-arm pilot study (Canadian Task Force classification II-2). SETTING: University-affiliated teaching hospital and private community hospital. PATIENTS: Women with a diagnosis of symptomatic uterine myomas planning to undergo hysterectomy. INTERVENTIONS: Seventy-three women underwent transabdominal ultrasound-guided HIFU treatment using a volumetric ablation technique referred to as "shell ablation," in which the HIFU energy is deposited in patterns that partially encapsulate the peripheral region of the targeted myoma(s). Patients were divided into 2 sequential cohorts, the development cohort (the first 37 patients treated) and the validation cohort (the final 36 patients treated). Development cohort treatments were performed for dose-ranging purposes to identify the optimum HIFU treatment parameters, whereas the validation cohort treatments were performed to validate these final settings. Sixty-five patients (89.0%) received only prophylactic oral, sublingual, or intramuscular analgesia before treatment, sometimes with oral anxiolytics. The remaining 8 patients (11.0%) were anesthetized before treatment. Sixty-seven patients (91.8%) then had scheduled hysterectomies between 0 and 179 days after treatment completion. Adverse events were monitored until study exit, which ranged from 10 to 191 days post-treatment. MEASUREMENTS AND MAIN RESULTS: The primary efficacy endpoint measured in all 73 patients was the nonperfused volume (NPV) of tissue produced, which was assessed between 0 and 7 days post-treatment either by tissue sectioning after hysterectomy or by gadolinium-enhanced magnetic resonance imaging. Secondary efficacy endpoints were also measured in subsets of patients who were prospectively scheduled for delayed hysterectomies: Changes in menstrual blood loss (MBL), symptom severity (SS), and quality of life (QOL) scores were assessed using validated techniques at 3 months post-treatment in 10 patients and changes in treated myoma volume were assessed using magnetic resonance imaging at 3 to 6 months post-treatment in 14 patients. In all 73 patients, there were no reports of any serious adverse device effects, including no damage to any extrauterine collateral tissues or the abdominal skin. In the development cohort, a mean NPV of 17.9 ± 24.9 cm3 (range, 0-123.0) was produced in a mean total treatment time of 4.9 ± 2.4 minutes (range, 1.1-11.3). These metrics improved in the validation cohort, where a mean NPV of 44.9 ± 58.5 cm3 (range, 0-284.7) was produced in a mean total treatment time of 3.6 ± 2.1 minutes (range, 1.5-9.5). In the subsets of patients with data available, there was a significant improvement in QOL score (median, 16.5 point increase; p = .011), an improving trend in SS score (median, 13.5 point decrease; p = .254), and a significant improvement in treated myoma volume (mean, 24.0% decrease; p = .013). In 8 patients who had above-average MBL scores at baseline and regular menstrual cycle lengths during follow-up, there was also a significant improvement in MBL score (median, 40.8% decrease; p = .035). CONCLUSION: Ultrasound-guided HIFU ablation with the prototype device demonstrated an excellent safety profile and produced clinically relevant NPVs in a mean total treatment time of under 4 minutes using the final validated treatment settings. Short-term clinical efficacy metrics assessed in subsets of patients were encouraging, and larger studies should be conducted to confirm these results (ClinicalTrials.gov, NCT01946178).