Baseline Fluctuations Research Articles

Semi-real-time removal of baseline fluctuations in electrocardiogram (ECG) signals by an infinite impulse response low-pass filter (IIR-LPF)

The suppression of baseline disturbance in electrocardiogram (ECG) is necessary to avoid distorting diagnostic features in the data. In order to remove baseline drift, digital filter specifications had been designing along with detrending fluctuation algorithms. However, all these methods require a high amount of off-line computation. To address this, we propose a new method to remove baseline drift in ECG signals with semi-real-time computation while compensating for the phase distortion from the frequencies in the passband of the infinite impulse response low-pass filter and estimating its sample delay for the filtered signal. Regarding evaluation of the proposed filter, we can find the fact that the signal-to-noise ratio increases by approximately 3 dB after applying the filter to the MIT-BIH stress data consisted of arrhythmias corrupted with the intentional baseline wander and the disturbances due to muscle interactions as well as electrode–skin impedance mismatch during the electrocardiogram recordings.

Compensation of the baseline temperature fluctuations for autonomous CE–C4D instrument working in harsh environments

One of the main problems of the remote complex sample analysis instrumentation is that such systems are susceptible to temperature fluctuations. Temperature regulation is energetically ineffective, and it is not used in most of the field portable analytical systems. Separations performed in a changing temperature environment provide electropherograms with considerable baseline fluctuations, resulting in significant errors in detection and integration of the peaks. This paper describes electropherogram baseline compensation that is suitable for the capillary electrophoresis-contactless conductivity detection analytical method. The baseline compensation utilizes linear or polynomial data processing methods, and can be programmed in-line using simple microcontroller, or on-line and off-line in data acquisition software. This method is targeted for field portable and autonomous analytical systems that are utilized in a fluctuating environment.

TraceSpecks: A Software for Automated Idealization of Noisy Patch-Clamp and Imaging Data

Experimental records of single molecules or ion channels from fluorescence microscopy and patch-clamp electrophysiology often include high-frequency noise and baseline fluctuations that are not generated by the system under investigation and have to be removed. Moreover, multiple channels or conductance levels can be present at a time in the data that need to be quantified to accurately understand the behavior of the system. Manual procedures for removing these fluctuations and extracting conducting states or multiple channels are laborious, prone to subjective bias, and likely to hinder the processing of often very large data sets. We introduce a maximal likelihood formalism for separating signal from a noisy and drifting background such as fluorescence traces from imaging of elementary Ca2+ release events called puffs arising from clusters of channels, and patch-clamp recordings of ion channels. Parameters such as the number of open channels or conducting states, noise level, and background signal can all be optimized using the expectation-maximization algorithm. We implement our algorithm following the Baum-Welch approach to expectation-maximization in the portable Java language with a user-friendly graphical interface and test the algorithm on both synthetic and experimental data from the patch-clamp electrophysiology of Ca2+ channels and fluorescence microscopy of a cluster of Ca2+ channels and Ca2+ channels with multiple conductance levels. The resulting software is accurate, fast, and provides detailed information usually not available through manual analysis. Options for visual inspection of the raw and processed data with key parameters are provided, in addition to a range of statistics such as the mean open probabilities, mean open times, mean close times, dwell-time distributions for different number of channels open or conductance levels, amplitude distribution of all opening events, and number of transitions between different number of open channels or conducting levels in asci format with a single click.

A Robust Self-navigation for Respiratory Gating in 3D Radial Ultrashort Echo-time Lung MRI using Concurrent Dephasing and Excitation

Three-dimensional ultrashort echo-time (UTE) imaging with radial k-space acquisition is a well-known MR imaging technique that generates comparable lung images to X-ray and computed tomography (CT). Although researchers have sought to minimize the incidence of motion artifacts, there is still a need to accomplish further reduction of motion artifacts through respiratory gating. In this study, we introduce a robust self-navigation for respiratory gating in 3D radial UTE lung imaging especially based on concurrent dephasing and excitation (CODE). To reduce the baseline fluctuation of self-navigated respiratory signals as well as the dependence on the position of the navigating echoes in the k-space trajectories, both of which originate from varying degrees of steadystate condition outside the fully excited regions of a spin system in CODE-MRI, we proposed a new self-navigation method which applies dual navigating echoes successively in the superior-inferior direction and takes the second navigating echoes for respiratory-motion tracking. The phantom and human experimental results showed that the proposed method successfully suppressed the baseline fluctuations of the navigating-echo signals and the resulting respiratory signals, thereby reducing the respiratory-motion artifacts like blurring in the human lung images thanks to the improved respiratory gating.

Motion Tolerant Unfocused Imaging of Physiological Waveforms for Blood Pressure Waveform Estimation Using Ultrasound.

This paper details unfocused imaging using single-element ultrasound transducers for motion tolerant arterial blood pressure (ABP) waveform estimation. The ABP waveform is estimated based on pulse wave velocity and arterial pulsation through Doppler and M-mode ultrasound. This paper discusses approaches to mitigate the effect of increased clutter due to unfocused imaging on blood flow and diameter waveform estimation. An intensity reduction model (IRM) estimator is described to track the change of diameter, which outperforms a complex cross-correlation model (C3M) estimator in low contrast environments. An adaptive clutter filtering approach is also presented, which reduces the increased Doppler angle estimation error due to unfocused imaging. Experimental results in a flow phantom demonstrate that flow velocity and diameter waveforms can be reliably measured with wide lateral offsets of the transducer position. The distension waveform estimated from human carotid M-mode imaging using the IRM estimator shows physiological baseline fluctuations and 0.6-mm pulsatile diameter change on average, which is within the expected physiological range. These results show the feasibility of this low cost and portable ABP waveform estimation device.

Circulating adiponectin modifies the FGF23 response to vitamin D receptor activation: a post hoc analysis of a double-blind, randomized clinical trial.

The fibroblast growth factor 23 (FGF23) response to phosphate load is suppressed in adiponectin gene null mice and substantially amplified in mice overexpressing the same gene and vitamin D receptor (VDR) activation markedly enhances FGF23 gene expression. We performed an analysis of the static (baseline adiponectin levels) and dynamic (fluctuations in adiponectin levels) interactions of serum adiponectin with the FGF23 response to paricalcitol and placebo in the setting of a double-blind, randomized clinical trial in chronic kidney disease (CKD) patients (NCT01680198). As compared with placebo, VDR activation by paricalcitol markedly increased serum FGF23 levels (P < 0.001), and such an increase was amplified in patients in the 4th adiponectin quartile as compared with other quartiles (P = 0.009) while no such an effect was noted in the placebo group (P = 0.49). Both baseline adiponectin (P for interaction = 0.009) and fluctuations in adiponectin levels following paricalcitol and placebo (P for interaction = 0.003) strongly modified the difference in the FGF23 response to these treatments. These interactions were specific because no similar effect modification by other factors with the FGF23 response to VDR activation was found. Furthermore, in a global correlation analysis, adiponectin and FGF23 were interrelated independent of the estimated glomerular filtration rate and other potential confounders (β = 0.22, P = 0.003). Adiponectin is a strong modifier of the FGF23 response to VDR activation in CKD patients. The adiponectin-FGF23 link discovered in genetically engineered mice is of mechanistic relevance in the FGF23 response to VDR activation in CKD patients.

High precision measurement of the Ne19β -decay half-life using real-time digital acquisition

The half-life of $^{19}$Ne has been measured using a real-time digital multiparametric acquisition system providing an accurate time-stamp and relevant information on the detectors signals for each decay event. An exhaustive offline analysis of the data gave unique access to experimental effects potentially biasing the measurement. After establishing the influence factors impacting the measurement such as after-pulses, pile-up, gain and base line fluctuations, their effects were accurately estimated and the event selection optimized. The resulting half-life, $17.2569\pm0.0019_{(stat)}\pm0.0009_{(syst)}$~s, is the most precise up to now for $^{19}$Ne. It is found in agreement with two recent precise measurements and not consistent with the most recent one [L.J. Broussard {\it et al.}, Phys. Rev. Lett. {\bf112}, 212301 (2014)] by 3.0 standard deviations. The full potential of the technique for nuclei with half-lives of a few seconds is discussed.

An Arrhythmia Classification Method in Utilizing the Weighted KNN and the Fitness Rule

BackgroundArrhythmia is the disturbance in the heart's regular rhythmic activity. Although arrhythmia signals are generally reflected on electrocardiogram records, some arrhythmias do not continuously appear. In such cases, heart-rate variability signals may have to be obtained over long periods of time and should be inspected by experts. However, analyses by experts require a long time and may omit important information. Therefore, computer aided diagnosis systems are required to automatically detect diverse types of arrhythmias. In addition, although many efforts have been made to develop arrhythmia detection techniques, studies on algorithms that are reliable, robust, and have an excellent adaptability to diverse situations remain necessary. ObjectiveIn this paper, we integrate coefficients extracted through principal component analysis (PCA) and linear discriminant analysis (LDA) for reinforcing the original signal's representative features and use the weighted k-nearest neighbor (WKNN) applying the weighted value control for reducing the sensitivity depending on the K size of k-nearest neighbor (KNN), and reclassify the data that were not accurately classified using the fitness rule for improving the arrhythmia classification accuracy. MethodsIn the preprocessing phase, the amplitude is adjusted through normalization and baseline fluctuations, and diverse noises existing in signals are removed using wavelets. In the feature extraction and selection phase, using daubechies 2, the pre-processed electrocardiogram signals are decomposed, and d4 and a4 feature coefficients are extracted. Thereafter, the dimensions of the d4 and a4 feature coefficients are reduced using PCA and LDA, respectively, and the resultant coefficients from the reduction are combined and composed as features. In the classification phase, the test data are classified into four classes using the KNN. The goodness of fit of the classified data is tested using the fitness rules, and any beats that are not classified correctly are reclassified by applying them to the WKNN algorithm. ResultsThe results show that sensitivity = 97.57%, specificity = 99.42%, and positive predictive value = 94.41% are exhibited, as well as slightly higher sensitivity, specificity, and positive predictive values than other results. ConclusionThe classification combining the features of PCA and LDA shows better results than classification using the features of PCA and LDA each. Additionally, the classification using WKNN and fitness rules exhibits higher sensitivity, specificity, and positive predictive values than classification without using WKNN and fitness rules thereby classifying arrhythmia more efficiently.

HGL: A hybrid global-local load balancing routing scheme for the Internet of Things through satellite networks

Satellite networks provide complete connectivity and worldwide data transmission capability for constructing the Internet of Things. However, because of the varying Internet of Things traffic density, satellite networks may endure imbalanced traffic requirements and frequent link congestion. To effectively resolve these problems and optimally transmit Internet of Things data, a novel hybrid global-local load balancing routing scheme for Low Earth Orbit satellite networks is proposed in this article. Hybrid global-local load balancing routing scheme enables satellites to route Internet of Things traffic through global planning and local real-time adjustments in two steps. In hybrid global-local load balancing routing scheme, given the predictive nature of Internet of Things traffic distribution and Low Earth Orbit satellite networks, the inter-satellite traffic demand is decomposed into a predictable long-range baseline and unpredictable short-range fluctuations. A global strategy is employed first for preliminary global traffic allocation based on long-range baselines, and a local strategy is then employed for route adjustments based on short-range fluctuations. With the combination of global planning and local real-time adjustments, network traffic can eventually obtain a near-optimal allocation. Numerical simulations indicate that in contrast to single-strategy schemes, hybrid global-local load balancing routing scheme can more thoroughly eliminate congestion, and it performs better in measures such as packet loss rate, average queuing delay, traffic distribution, route oscillation, and communication overhead.

Capillary electrophoresis coupled to contactless conductivity detection for analysis of amino acids of agricultural interest in composting.

Composting is a sustainable approach to manage animal and vegetal waste generated in the Fundação Parque Zoológico de São Paulo. The resulting compost is often used in ZOO's premises as an organic fertilizer for the production of vegetables, which is further used to feed the animals. The composting product provides many forms of mineral and also amino acids (AA) that are absorbed by plants as nutrients. Since most amino acids absorb only slightly or not at all in the UV wavelengths, we developed a method for the determination of AA of agricultural interest in the composting samples. Due to the complexity of samples, we used ion exchange chromatography for the purification of AA prior to analysis. The proposed CZE-C4 D method allowed a separation of the AA in a short analysis time (less than 3.0 min), with great linearity (with R2 ranging from 0.993 to 0.998). Using a BGE of 10 mmol/L TEA, reduction of high-frequency noise and lower baseline fluctuations were obtained. The LOQ for the five AA were around 35 μmol/L, and were adequate for our purpose. In addition, the method showed good precision (RSD of peak area and migration time less than 1.55 and 1.16%, respectively).

Analog filtering methods improve leading edge timing performance of multiplexed SiPMs

Multiplexing many SiPMs to a single readout channel is an attractive option to reduce the readout complexity of high performance time of flight (TOF) PET systems. However, the additional dark counts and shaping from each SiPM cause significant baseline fluctuations in the output waveform, degrading timing measurements using a leading edge threshold. This work proposes the use of a simple analog filtering network to reduce the baseline fluctuations in highly multiplexed SiPM readouts. With 16 SiPMs multiplexed, the FWHM coincident timing resolution for single mm LYSO crystals was improved from 401 ± 4 ps without filtering to 248 ± 5 ps with filtering. With 4 SiPMs multiplexed, using an array of mm LFS crystals the mean time resolution was improved from 436 ± 6 ps to 249 ± 2 ps. Position information was acquired with a novel binary positioning network. All experiments were performed at room temperature with no active temperature regulation. These results show a promising technique for the construction of high performance multiplexed TOF PET readout systems using analog leading edge timing pickoff.

Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo.

Extracting neuronal spiking activity from large-scale two-photon recordings remains challenging, especially in mammals in vivo, where large noises often contaminate the signals. We propose a method, MLspike, which returns the most likely spike train underlying the measured calcium fluorescence. It relies on a physiological model including baseline fluctuations and distinct nonlinearities for synthetic and genetically encoded indicators. Model parameters can be either provided by the user or estimated from the data themselves. MLspike is computationally efficient thanks to its original discretization of probability representations; moreover, it can also return spike probabilities or samples. Benchmarked on extensive simulations and real data from seven different preparations, it outperformed state-of-the-art algorithms. Combined with the finding obtained from systematic data investigation (noise level, spiking rate and so on) that photonic noise is not necessarily the main limiting factor, our method allows spike extraction from large-scale recordings, as demonstrated on acousto-optical three-dimensional recordings of over 1,000 neurons in vivo.

The data acquisition system of the Latin American Giant Observatory (LAGO)

LAGO is an extended cosmic ray observatory composed of water-Cherenkov detectors (WCD) placed throughout Latin America. It is dedicated to the study of various issues related to astrophysics, space weather and atmospheric physics at the regional scale. In this paper we present the design and implementation of the front-end electronics and the data acquisition system for readout of the WCDs of LAGO. The system consists of preamplifiers and a digital board sending data to a computer via an USB interface. The analog signals are acquired from three independent channels at a maximum rate of ~1.2×105 pulses per second and a sampling rate of 40MHz. To avoid false trigger due to baseline fluctuations, we present in this work a baseline correction algorithm that makes it possible to use WCDs to study variations of the environmental radiation. A data logging software has been designed to format the received data. It also enables an easy access to the data for an off-line analysis, together with the operational conditions and environmental information. The system is currently used at different sites of LAGO.

Introducing a combined approach of empirical mode decomposition and PCA methods for maternal and fetal ECG signal processing

Objectives: The purpose of this study was to evaluate the effectiveness of the non-linear adaptive combined approach on the analysis of maternal and fetal signals corrupted by noise.Methods: Empirical mode decomposition (EMD) is a non-linear adaptive technic for data analysis and has been widely used in biomedical data. When we apply EMD on ECG signals, the number of modes that contain cardiac information may vary regarding the subject, type of the signal and recording conditions. This fact can cause some difficulties in signal reconstruction and noise removal using the derived modes. For overcoming this issue, we designed a method to combine principal component analysis (PCA) method with EMD to remove the correlation between the calculated modes and provide a smaller set of uncorrelated orthogonal.Results: We have developed a combined method that proves the power of using PCA on the output of EMD method. The combined method reduces the power of oscillatory artifacts of the baseline. Thus, the PCA-EMD combination provides a noise-free signal.Conclusions: The combination of EMD and PCA methods worked well in being adaptive (from of EMD) and reconstruction (from PCA). It has been proved that this combined method is helpful in separating the signal components, especially in extracting the pure data from the baseline fluctuations.

Near-infrared spectroscopy to define cognitive frontal lobe functions.

Near-infrared spectroscopy (NIRS) monitors changes in the regional cerebral oxygenation (rSO) and has been used to study cerebral physiologic functions in normal states and during epileptic seizures. Yet, the limitations and pitfalls of the technique are not fully understood. The authors evaluated NIRS changes over the frontal lobes during language tasks known to be associated with the integrity of the dominant frontal lobe in 17 normal adults (handedness: 14 right, 3 left). Recording protocol involved a baseline (3 minutes) with the subject relaxed and thinking of a blue sky and a second baseline during voluntary mouth movements mimicking speech. Two standardized neuropsychological word-generation tasks (controlled word-association tests: CFL and Animals) were then administered (4 minutes total) followed again by the two baseline procedures. Mouth movement without verbalization increased rSO values in excess of 2 SD of baseline fluctuations in 70% of the subjects. A t-test comparison of these baseline measurements was statistically significant (P < 0.0001). A general linear model repeated-measures procedure was then used to statistically examine NIRS increments during the cognitive tasks above and beyond the contribution produced by mouth movements during the second baseline. Compared to the second baseline, rSO further increased significantly during the word generation tasks (left frontal F value = 21.4, P < 0.0001; right frontal F value = 15.2, P < 0.001), confirming the utility of the technique. There was no apparent difference related to handedness. These findings corroborate the usefulness of NIRS to demonstrate focal cerebral activation during an "executive" language task. However, interpretation of changes can be confounded by extracerebral factors such as mouth movement, a finding of particular relevance in NIRS clinical applications.

A new technique for determining critical micelle concentrations of surfactants and oil dispersants via UV absorbance of pyrene

Abstract The conventional UV-based methods for determining the critical micelle concentration (CMC) of surfactants often fail for low-solubility surfactants or mixtures of surfactants/solvents or oil dispersants due to baseline uncertainty of the UV spectra. To overcome the limitations, we proposed and tested a new UV-based approach and found that the surfactant concentration, at which the incipient red shift of the strongest UV absorbance peak of pyrene occurs, can be used to quickly and roughly locate the range of the CMC for the surfactant. Furthermore, we developed a more robust and accurate method, which can accurately pinpoint the CMC graphically by following the change of the maximum measurable peak difference (i.e., the strongest UV absorbance peak minus a weaker reference peak) as a function of the surfactant concentration. Regardless of the baseline fluctuations, the method was able to accurately determine CMCs of 8 model surfactants and oil dispersants. Based on the UV-absorbance analysis, the ratio of pyrene to surfactant molecules in micelles was estimated, which further reveals the roles and abilities of various surfactants in dissolution/dispersion of pyrene or other PAHs in water. The new method can be used to measure CMCs of a wide range of surfactants and oil dispersants.

Dexmedetomidine: A Preliminary Exploration of its Safety and Efficacy in Pediatric Dental Setting

Objective: To report on safety and efficacy of intravenous usage of Dexmedetomidine for endodontic intervention in young and anxious pediatric patients. Methods: This prospective pilot investigation enrolled 10 healthy ASA status I, 2-6 year old children who were anxious (Venham’s score ≥4) and were scheduled to undergo primary molar pulpectomy under sedation. Sedation induction was done with 1 mg/kg of propofol bolus followed by 0.2-0.8 μg/kg of dexmedetomidine infusion for maintenance. Sedation was titrated to achieve Houpt’s overall behavior score of ≥4. In case of insufficient sedation, rescue propofol boluses (1 mg/kg) were administered. Vitals were monitored every 5 minutes and recovery was evaluated using Alderete Modified Post Anesthesia Discharge Scoring System. Adverse events, i.e., ≥ ±20% baseline fluctuations in vital signs, tachycardia, bradycardia, apnea, desaturation, stridor and/or laryngospasm were recorded. Results: The procedure was successfully completed in all of the subjects with the current sedation regime as per the study protocol. Rescue propofol boluses were needed in 8 subjects. No untoward fluctuations in vital signs or adverse events were reported in either intra-operative phase or post-operatively. Conclusion: Intravenous Dexmedetomidine is safe and efficient sedative for endodontic intervention in young and anxious pediatric patients.

Variability of FEV1 and criterion for acute pulmonary exacerbation.

Morgan et al. (1) concluded that cystic fibrosis (CF) in children and adolescents with a high baseline forced expiratory volume (FEV1) were less likely to have a therapeutic intervention or slower rate of FEV1 decline after a single acute decline in FEV1 of 10%. This conclusion is not well supported due to the arbitrary criteria used for defining a pulmonary exacerbation, as explained below. First, only a single low FEV1 value defined an exacerbation. However, FEV1 measurements are notoriously variable from test-to-test; Taylor-Robinson et al. (2) showed that the baseline fluctuations have a wide range of about 60%. FEV1 tests are sensitive to time of day, health status, mood, tiredness, lack of sleep, medical instruction, nutritional status, acute comorbidities, and other factors Cystic Fibrosis Foundation (3). Given that a single FEV1 assessment was used, rather than the average of repeated measurements on different days, evidence that the assessment values were technically accurate. Second, an exacerbation was defined as a single 10% decline in FEV1 in the above study without any explanation as to why 10% was chosen nor why a range of declines were not evaluated to determine the sensitivity and specificity of different criteria (by testing several criterion values such as 5, 15, 20, and 25%). A threshold of 10% is nearly within the noise level of the FEV1 measurements (2, 4). This leaves open the possibility that the findings in the study would not hold if a slightly greater (or smaller) value was used, such as 8 or 12%. Furthermore, regarding the use of the cutoff of 10%, there is no agreement on the optimal cutoff for separating pulmonary exacerbations from the large natural technical variations in FEV1 from test-to-test, a variation that has been found to be higher in CF without evidence of concomitant changes in the severity of the condition (4, 5). National treatment guidelines (5) for acute pulmonary exacerbations in CF was based on the work of Fuchs et al. (6), a clinical trial of DNAase that only incidentally mentioned 10% as a criterion if 4 of 12 other signs or symptoms were present in a population of adults and children. In a more comprehensive study on children under six years of age, Rabin et al. (7) and Regelmann et al. (8) defined exacerbations operationally by whether or not pulmonologists decided to intensify treatment using antibiotics. These authors found the average FEV1 decline to be 20% in children under 6 years of age, these investigators proposed a refinement of the criterion to 15% or higher, rather than 10% suggested by Fuchs et al. (6), under the condition that a 15% decline would only be considered an exacerbation if two other clinical signs were concurrent, such as increased cough frequency, new crackles, or hemoptysis. Evidence on the best cutoff value is consequently nearly absent and remains to be determined. The most logical path follow would be to first test the full range of pulmonary decline criterion, perhaps from 0 to 30%, to determine the optimal criterion, and then to conduct a focused study on this value. The findings from such a range analysis could be of great value in helping further refine the criterion for an exacerbation based on FEV1 decline, rather than assuming a single value at this early stage. The study has many prominent strength including well-defined hypotheses, very large sample size, analysis by age group, excellent statistical analysis, clearly presented findings, excellent flow of logic, and others. However, due to the shortcomings described above, we suggest further study of the above critical questions before the findings are implemented in practice.

Self-organization on social media: endo-exo bursts and baseline fluctuations.

A salient dynamic property of social media is bursting behavior. In this paper, we study bursting behavior in terms of the temporal relation between a preceding baseline fluctuation and the successive burst response using a frequency time series of 3,000 keywords on Twitter. We found that there is a fluctuation threshold up to which the burst size increases as the fluctuation increases and that above the threshold, there appears a variety of burst sizes. We call this threshold the critical threshold. Investigating this threshold in relation to endogenous bursts and exogenous bursts based on peak ratio and burst size reveals that the bursts below this threshold are endogenously caused and above this threshold, exogenous bursts emerge. Analysis of the 3,000 keywords shows that all the nouns have both endogenous and exogenous origins of bursts and that each keyword has a critical threshold in the baseline fluctuation value to distinguish between the two. Having a threshold for an input value for activating the system implies that Twitter is an excitable medium. These findings are useful for characterizing how excitable a keyword is on Twitter and could be used, for example, to predict the response to particular information on social media.

Improvements in the performance of an incubation-type planar patch clamp biosensor using a salt bridge electrode and a plastic (PMMA) substrate

Incubation-type planar patch clamp biosensors, first described in 2008, are expected to enable the realization of high-throughput neural network screening. Several technical challenges must be overcome before this technique may be implemented. First, it is difficult to achieve a sufficiently high seal resistance (a gigaohm seal), which is an important parameter for patch clamp operation. A low seal resistance produces large baseline fluctuations corresponding to the fluctuation of the solid–liquid and liquid–liquid interface potentials. Second, the sensor cell must be positioned at a micropore over a long incubation time while maintaining the cell viability. Finally, a low-cost high-performance sensor chip suitable for high-throughput screening must be developed. These problems have been resolved to some extent in the present work. A stable electrode with a salt bridge structure was developed here to reduce the baseline fluctuations. The cell positioning technology was improved by forming a novel cell trapping pattern using hot embossing on a plastic (polymethylmethacrylate (PMMA)) substrate for use in a microfluidic sensor chip. The combination of the stable electrode and the cell trapping pattern dramatically increased the device success probability from ∼2% to 60–80% using HEK293 cells as a model system. The utility of the present results was tested by characterizing rat hippocampal neuron networks. The seal resistance was found to be lower than the seal resistance obtained from the HEK293 cells. The effectiveness of the stable electrodes, however, was significantly clear and spontaneous channel currents from the neural network were successfully observed.