Signal Filtering Research Articles

A Superconducting Dual-Band Bandpass Filter for IF Signals of Multi-Frequency Millimeter-Wave Atmospheric Spectrometer

The high temperature superconductor (HTS) dual-band bandpass filter (DB-BPF) has been developed for microwave intermediate frequency (IF) signals (8-12 GHz) of a multi-frequency millimeter-wave atmospheric spectrometer. The HTS DB-BPF consists of 6-pole and 12-pole BPFs with an 8.348 GHz center frequency and 0.27 GHz band width and an 11.156 GHz center frequency and 1.46 GHz band width, respectively. The HTS DB-BPF was fabricated using YBa <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Cu <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> O <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">_y</i> thin films on R-Al <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> substrate. Fabricated DB-BPF is evaluated by experiment and simulation with good agreement. We started the long-term monitoring of atmospheric molecular species using DB-BPF at Syowa station in Antarctica.

Cell-Straddling Robust-Fast Cross-Correlation Mitigation via MMSE Filter for DSSS Signals

Existing cross-correlation mitigation algorithms based on the minimum mean square error (MMSE) criterion can effectively suppress multiple access interference (MAI) but suffer from high complexity and modeling grid mismatch. In this work, we propose a cell-straddling robust-fast cross-correlation mitigation (CSR-FCCM) algorithm with two improvements. First, CSRFCCM combines the two-dimensional joint iterative adaptive filtering with interference cancellation, which significantly reduces the number and computational cost of complex amplitude MMSE filters. Second, two discriminators are designed to estimate the straddling offset of delay and frequency for the direct sequence spread spectrum (DSSS) signal. The mismatch problem can be ameliorated by substituting estimated straddling offsets into the signal model, which further improves the MAI mitigation effect. The effectiveness of the CSR-FCCM is verified by simulations using 1023- and 63- length Gold codes. Simulation results show that CSR-FCCM has a better MAI mitigation performance and a lower complexity than the open-loop MAI mitigation algorithms, including 2D-JIAF, and RSR-APC.

Near-Ideal Predictors and Causal Filters for Discrete-Time Signals

Near-Ideal Predictors and Causal Filters for Discrete-Time Signals

Selection of the bandwidth of the «raised cosine» shaping filter for navigation meander signals

Problem statement. One of the ways to reduce the level of out-of-band radiation when generating navigation signals is to use a "raised cosine" type filter. However, the issues of the formation of meander navigation signals using the "raised cosine" filter have not been fully investigated. In particular, the question of choosing the frequency band of the "raised cosine" type filter remains open. Purpose. Evaluation of the influence of the bandwidth of the "raised cosine" forming filter on the spectral and temporal characteristics, the energy efficiency of the transmitter, as well as the integrity of the structural and temporal parameters of navigation meander signals. Results. Analytical expressions for the pulse characteristic of the "raised cosine" type filter are obtained, taking into account the parameters of meander signals. The influence of the frequency band of the "raised cosine" filter on the distortion of meander signals in the frequency and time domain is estimated by mathematical modeling. It is shown that for the formation of meander signals in the "raised cosine" filters, it is advisable to choose the maximum frequency band, which ensures minimal distortion in the frequency and time domains, the minimum value of the peak factor and the best characteristics of the integrity of the structural and temporal parameters of the signals. Practical significance. The results can be used by specialists in the field of satellite radio navigation in the modernization of global navigation satellite systems.

IMPROVING THE QUALITY OF THE FUNCTIONING OF TELECOMMUNICATION SYSTEMS BASED ON THE INTEGRATION OF NEURAL NETWORKS

The article proposes the integration of neural networks as a parallel element base in telecommunications systems. In this case, their main advantage, the ability to self-study or adapt to external conditions, will be used. For telecommunication systems in conditions of interference, this ability will significantly increase their noise immunity, reliability, operability, etc. The article considers an example of integration of a neural network into a discrete matched signal filter. It is noted that the use of parallel mathematics in signal processing, such as a system of residual classes, will lead to the maximum effect of increasing the quality parameters of such elements of telecommunications.&#x0D; Purpose – introduction to neural networks; application of neural networks in digital filtering; possible directions of integration of neural network technologies.&#x0D; Method or methodology of the work: harmonic analysis, Fourier transform, correlation analysis were used in the article.&#x0D; Results: The introduction of mass parallelism in telecommunications becomes feasible when integrating neural networks into telecommunication elements. The efficiency becomes maximum when using simultaneously parallel mathematics of the system of residual classes&#x0D; Practical implications: the use of parallel mathematics in signal processing, such as a system of residual classes, will lead to the maximum effect of increasing the quality parameters of such elements of telecommunications.

Improvement of microprocessor voltage control relay operation algorithms for single-phase household consumers

This paper pays attention to a single-phase voltage control relays work algorithms that are used for protection of the household consumers of electrical energy from unacceptable voltage deviations within power supply network. An overview, analysis and description of operation algorithms, voltage measurements and thresholds of current voltage control relays, based on microprocessors and microcontrollers have been carried out. The conducted overview and analysis systematizes information on the technical and functional features of the operational design, work algorithms, circuits and components of the mentioned relays and demonstrates the prospects for development of voltage relay operational algorithms and protective characteristics according to existing International standards. The protective characteristics and standards of power quality have been outlined and illustrated by the authors in detail. The voltage measuring and digital signal processing (signal filtering) algorithms in modified voltage relay are described as well. Also represented a novel approach in design of operation algorithms taking into account of positive sides in existing voltage control relays and new sintesed algorithms including concept of voltage measurement and decision making algorithms for a new single-phase voltage control relays for household consumers. A generalization and conclusion are made concerning the improved operation algorithm in the voltage control relay for protection of household consumers.

Rotor Position Estimation for Permanent Magnet Synchronous Machines using Electromotive Force and Anisotropy Using Extended-Kalman-Filter

In this paper a new rotor position observer for permanent magnet synchronous machines (PMSM) based on an Extended-Kalman-Filter (EKF) is presented. With this method, just one single EKF is sufficent to evaluate the position information from electromotive force (EMF) and anisotropy. Thus, the PMSM can be controlled for the entire speed range without a position sensor and without the need to switch or synchronize between different observers. The approach covers online estimation of permanent magnetic field and mechanical load. The resulting EKF-based rotor position estimator is embedded in the existing cascaded control concept of the PMSM without need of additional angle trackers or signal filters. The experimental validation for the position sensorless control shows optimized dynamic behaviour.

Application of Aeromagnetic Data Analysis and Interpretations to Investigate Solid Mineral Potential in Part of Bauchi, Northeast Nigeria

Abstract: The distribution of surface and subsurface magnetic materials within the study area, the delineation of geologic lineaments, and an estimate of the depth to magnetic sources were all determined by interpreting high resolution aeromagnetic data that covered a portion of Bauchi, northeastern Nigeria, lying between Latitudes 9040'00"N to 10010'0"N and Longitudes 900'0"E to 9040'0'E. The Aeromagnetic map, analytical signal, and horizontal derivative filters used on total magnetic intensity data after reduction to the magnetic equator (RTE) show that the Toro and its environs contain highly magnetic minerals thought to be potential deposits of iron ore. The lithological map and the lineament maps have a good connection. Further examination of the findings reveals that the research area has varying degrees of Ferro-, para-, and diamagnetic mineralization (of the iron and non-iron varieties). The geological source bodies are thought to be located between 177.389 and 991.626 meters deep, according to the Euler depth solution. This shows that during the orogenic process, a sequence of strong deformations were present alongside the Toro.

Development and validation of a model for measuring alcohol consumption from transdermal alcohol content data among college students.

Transdermal alcohol content (TAC) data collected by wearable alcohol monitors could potentially contribute to alcohol research, but raw data from the devices are challenging to interpret. We aimed to develop and validate a model using TAC data to detect alcohol drinking. We used a model development and validation study design. Indiana, USA PARTICIPANTS: In March to April 2021, we enrolled 84 college students who reported drinking at least once a week (median age = 20 years, 73% white, 70% female). We observed participants' alcohol drinking behavior for 1week. Participants wore BACtrack Skyn monitors (TAC data), provided self-reported drinking start times in real time (smartphone app) and completed daily surveys about their prior day of drinking. We developed a model using signal filtering, peak detection algorithm, regression and hyperparameter optimization. The input was TAC and outputs were alcohol drinking frequency, start time and magnitude. We validated the model using daily surveys (internal validation) and data collected from college students in 2019 (external validation). Participants (N = 84) self-reported 213 drinking events. Monitors collected 10915 hours of TAC. In internal validation, the model had a sensitivity of 70.9% (95% CI = 64.1%-77.0%) and a specificity of 73.9% (68.9%-78.5%) in detecting drinking events. The median absolute time difference between self-reported and model-detected drinking start times was 59 min. Mean absolute error (MAE) for the reported and detected number of drinks was 2.8 drinks. In an exploratory external validation among five participants, number of drinking events, sensitivity, specificity, median time difference and MAE were 15%, 67%, 100%, 45 minutes and 0.9 drinks, respectively. Our model's output was correlated with breath alcohol concentration data (Spearman's correlation [95% CI] = 0.88 [0.77, 0.94]). This study, the largest of its kind to date, developed and validated a model for detecting alcohol drinking using transdermal alcohol content data collected with a new generation of alcohol monitors. The model and its source code are available as Supporting Information (https://osf.io/xngbk).

Thick-film – a mature technology at the cutting edge of advances in the electronics industry

For decades, thick-film technology has proven to be a dependable, cost-efficient method for highly reliable electronic circuitry and components. Hybrid microelectronics was the first major application for fired thick-film materials, finding its way into military and aerospace applications, where reliability is paramount. Inner and outer electrodes for passive components have been another traditional thick-film market. One of the main advantages of thick film is that it is an additive process, where the various conductor, resistor, and dielectric pastes are screen-printed and fired or cured in succession to form the circuit. This results in cost-efficient processing for the circuit manufacturer. Patterned screens are relatively easy to manufacture, allowing for flexibility in circuit design, and screen printing allows for flexibility in feature sizes from hundreds of microns down to 30 microns or less. The main drivers in electronics today are miniaturization – higher circuit density, adaptation to new forms such as 3D and flexible substrates, and ecological factors such as reduced energy consumption, waste reduction, and reduction in the use of toxic substances (RoHS – REACH). Thick film has evolved to address these main drivers and due to its reliability, flexibility, and adaptability, The technology has found new applications. 5G telecommunications utilizes highly conductive silver coatings on signal filters for low losses. Automobiles have historically used thick film technology in fuel/air sensors, air bag deployment sensors, and electronic control units (ECUs). Current vehicles have become computers on wheels and have multiple driver assistance sensors (ADAS), e.g. lane departure warning, blind spot monitoring, automatic braking, regenerative braking, and fully autonomous driving. Both fired and non-fired thick-film technology is enabling these developments. Also in the automotive space, applications include thick film heaters for cabin comfort, heaters keeping ADAS sensors free from frost and snow, and heaters for battery management systems (BMS) in electric vehicles. Polymer thick-film (PTF) pastes for cured (90 – 250o C) electronic circuitry on temperature sensitive polymers have also been around for decades, used in membrane touch-switch keypads and similar circuity. Recently, new applications have emerged for PTF in printed electronics, where the ability to develop flexible, highly durable pastes is enabling new applications in flexible displays, medical monitoring, and performance enhancement in sports. As the megatrends continue to drive the advancement in technologies, the versatility, reliability, and adaptability of thick-film technology is expected to continue to facilitate these advancements. Heraeus Electronics, with its extensive portfolio of thick-film pastes and matched systems, is primed to support these advancements.

Spatially Addressable Multiplex Biodetection by Calibrated Micro/Nanostructured Surfaces

A challenge of any biosensing technology is the detection of very low concentrations of analytes. The fluorescence interference contrast (FLIC) technique improves the fluorescence-based sensitivity by selectively amplifying, or suppressing, the emission of a fluorophore-labeled biomolecule immobilized on a transparent layer placed on top of a mirror basal surface. The standing wave of the reflected emission light means that the height of the transparent layer operates as a surface-embedded optical filter for the fluorescence signal. FLIC extreme sensitivity to wavelength is also its main problem: small, e.g., 10 nm range, variations of the vertical position of the fluorophore can translate in unwanted suppression of the detection signal. Herein, we introduce the concept of quasi-circular lenticular microstructured domes operating as continuous-mode optical filters, generating fluorescent concentric rings, with diameters determined by the wavelengths of the fluorescence light, in turn modulated by FLIC. The critical component of the lenticular structures was the shallow sloping side wall, which allowed the simultaneous separation of fluorescent patterns for virtually any fluorophore wavelength. Purposefully designed microstructures with either stepwise or continuous-slope dome geometries were fabricated to modulate the intensity and the lateral position of a fluorescence signal. The simulation of FLIC effects induced by the lenticular microstructures was confirmed by the measurement of the fluorescence profile for three fluorescent dyes, as well as high-resolution fluorescence scanning using stimulated emission depletion (STED) microscopy. The high sensitivity of the spatially addressable FLIC technology was further validated on a diagnostically important target, i.e., the receptor-binding domain (RBD) of the SARS-Cov2 via the detection of RBD:anti-S1-antibody.

ECG-MAKE: An ECG signal delineation approach based on medical attribute knowledge extraction

The electrocardiogram (ECG) signal is made up of sequences of three distinct waves, including the P-wave, QRS-complex, and T-wave. These sequences may contain several different varieties of feature representation, which means various appearances represent different attribute knowledge of heart activity. Consequently, delicate analysis of the ECG attribute knowledge is critical, which focuses on empowering computers to understand ECG signals in a way physicians do. Traditional ECG systems usually only focus on the key wave detection or sub-sequences morphological classification, and the complex ECG features make the analysis process difficult to handle both tasks. In this paper, our goal is to propose a novel ECG analysis technique for ECG medical attribute knowledge feature extraction, termed ECG-MAKE method. The ECG-MAKE method mainly addresses two challenging issues—ECG signal key points detection and morphological delineation—by introducing four modules: signal preprocessing, key point detection, adaptive error correction, and attribute knowledge extraction. Signal preprocessing is based on a wavelet multi-resolution algorithm, which extracts both time and frequency domain information simultaneously, and achieves the goal of enhancing raw signals by filtering signals below 1 Hz and above 100 Hz. The key point detection combines mean-value difference and sliding window to detect R-peak. And according to the R-peak, further utilizes the ECG rules and threshold to detect the onset, peak, and offset of different heartbeat waveforms such as the P-waves and T-waves. Then, for standard 12-lead ECG, the adaptive error correction can automatically correct the spatial position of certain leads missed and false detection key points. Finally, the attribute knowledge extraction module is based on the statistical features of key points to obtain the ECG attributes knowledge of clinical diagnosis of ECG. Extensive experiments conducted on the publicly available database QT database (99.57% F1-score) have demonstrated the effectiveness of the proposed ECG-MAKE method. The proposed method has a higher classification performance than current state-of-the-art methods with an F1-score performance of 94.30% on the ZZU-ECG database.

A new OMA method to perform structural dynamic identification: numerical and experimental investigation

Operational modal analysis (OMA) methods are nowadays common in civil, mechanical and aerospace engineering to identify and monitor structural systems without any knowledge on the structural excitation provided that the latter is due to ambient vibrations. For this reason, OMA methods are embedded with stochastic concepts and then it is difficult for users that have no-knowledge in signal analysis and stochastic dynamics. In this paper an innovative method useful for structural health monitoring (SHM) is proposed. It is based on the signal filtering and on the Hilbert transform of the correlation function matrix. Specifically, the modal shapes are estimated from the correlation functions matrix of the filtered output process and then the frequencies and the damping ratios are estimated from the analytical signals of the mono-component correlation functions: a complex signals in which the real part represents the correlation function and the imaginary part is its Hilbert transform. This method is very simple to use since requires only few interactions with the users and thus it can be used also from users that are not experts in the aforementioned areas. In order to prove the reliability of the proposed method, numerical simulations and experimental tests are reported also considering comparisons with the most popular OMA methods.

Metasurface spatial filters for multiple harmonic signals

Abstract Nonlinear frequency mixings have shown an alternative way to create new electromagnetic sources in frequency ranges that are difficult to access with conventional techniques. To simultaneously use the fundamental frequency pump beam and multiple harmonic signals generated in the same channel, a device capable of separating each frequency component is required. Here, we propose and experimentally demonstrate metasurface-based spatial filters for the pump frequency and multiple harmonic frequencies. The metasurface was designed using eight different split ring resonator-based phase elements with 45° phase spacing, which allows wavefront shaping. The metasurface designed to have a one-dimensional gradient phase array produces cross-polarized reflection waves with different beam steering angles at the third- and fifth-harmonic frequencies (15 and 25 GHz) and operates as a metallic mirror at the fundamental frequency of 5 GHz. Our work suggests a new method to enable simultaneous use of broadband multi-frequency sources based on nonlinear frequency mixing.

Influence of the transition layer material on the etched pattern of multilayer films

High-quality frequency-selective surfaces (FSSs) exert a crucial role in the absorption and filtration of electromagnetic signals. FSS is made from structure-function-integrated materials with a patterned metal layer cover. Cr or Ni transition layers are usually arranged between the material substrate and the metal layer to enhance their bonding. However, the study on the removal behavior of Al/glass and Al/Ni/glass films by laser ablation with a pulse width of 100 ns of the 1064 nm laser found that the Ni transition layer increases the damage threshold of Al films because its thermophysical parameters changed the laser absorption rate of the Al surface and the spatial temperature distribution inside the Al film. The experimental results show that four characterized areas in the laser ablation surface are identified in the machined grooves when the laser energy density is 12 J/cm2, indicating that the multilayer films are mainly removed by vaporization, phase explosion, melting, and fragmentation. It is found that the removal mechanism of the Al/Ni/glass system is dominated by melting heat stress and fragmentation, so splashing is obvious and results in residual recondensation droplets of micrometer size. The above results provide ideas and methods for other high-quality laser processing of structure-function-integrated film systems.

Symmetrical Components Digital Filters for Microprocessor-Based Protection Input Signals

In microprocessor protections, measuring bodies are used that react to individual symmetrical components of signals or a combination of them. This makes the corresponding protection devices more sensitive. Of all the varieties of digital filters of symmetrical components, filters of the negative and zero sequences are mainly used. As for the known algorithms of their software implementation, it is advisable to use filters that form orthogonal components of the required sequence from orthogonal components of phase or phase-to-phase values of signals. Digital Fourier filters, characterized by inertia, are used as formers of the latter. For this reason, their transient modes are accompanied by the appearance of a dynamic error, which can significantly affect the functioning of filters of symmetrical components, worsening their properties. A significant reduction in this effect can be achieved by using shapers with correction of dynamic errors to isolate the orthogonal components of the input signals. They are based on non-recursive digital Fourier filters, the orthogonal components of which are subjected to software correction processing in order to obtain equivalent components characterized by fast-fading dynamic amplitude errors. Correction of the dynamic phase error is realized in the process of obtaining the resulting orthogonal components, which are a combination of Fourier components and calculated ones that have been estimated according to them. Based on the information about the amplitudes and current phases of the signals contained in the equivalent and resultant components, respectively, the resulting orthogonal components are formed, differing in minimal amplitude and phase errors in transient modes. According to these components, the orthogonal components of the signal of the negative and zero sequences in the corresponding filter are calculated. In the dynamic modeling environment of MATLAB-Simulink-SimPowerSystems, a digital model is implemented, which includes a power system, a three-phase group of current transformers, a load, a short-circuit block, as well as models of negative and zero sequence filters. The study of the functioning of these filters was carried out using two types of test actions, viz. a three-phase system of sinusoidal signals and a three-phase system of signals close to real secondary currents in short circuits. The results of the research have demonstrated that the developed digital filters of the negative and zero sequences have 1.1–1.4 times higher performance as compared with similar Fourier filters accepted as reference and that they are distinguished by improved magnitudes of dynamic indicators.

Acceleration sensitivity of piezoelectric pressure sensors and the influence on the measurement of explosion pressures

To measure the explosion pressure inside an enclosure, it is common to install a piezoelectric pressure sensor in the enclosure wall. The pressure wave of the internal explosion inevitably leads to vibrations of the enclosure walls. This unwanted but naturally occurring motion is also transmitted to the pressure sensor mounted in the enclosure wall and results in inertial forces affecting the piezoelectric element. During the measurement of the explosion pressure, this affects the output signal of the pressure sensor since an undesired signal due to the acceleration of the pressure sensor is superimposed on the desired pressure signal. This behaviour of the sensor is described as acceleration sensitivity. The level of acceleration sensitivity depends on the type and construction design of the pressure sensor. Even though this sensor behaviour is basically not a new phenomenon, the evaluation of an international comparison between Ex testing laboratories in the field of flameproof enclosures has shown that the consideration of this issue is a major challenge in daily practice concerning the measurement of explosion pressures and is even often completely neglected.This work evaluates the behaviour of various piezoelectric pressure sensors with respect to the influence of acceleration and investigates the specific impact on the explosion pressure measurement in the field of flameproof enclosures. For this purpose, explosions from typically used explosive mixtures such as hydrogen, propane and ethyne in air are examined. These investigations involve simple model enclosures with various specifications as well as a commercially available equipment for hazardous areas. By using blind holes and specially designed adapters, a practical method is applied to be able to detect the effect of acceleration on the sensor signal separately from the pressure signal. For this purpose, both the discrete-time pressure curves and the frequency components are analysed using Fast Fourier Transform. The use of signal filters as a practical and fast approach to address these unwanted signal components is discussed and evaluated.This paper provides guidelines for typical end-users in the field of flameproof enclosures how to handle acceleration of piezoelectric pressure sensors and the influence on the measurement of explosion pressures correctly.

Harmonic-Gaussian double-well potential stochastic resonance with its application to enhance weak fault characteristics of machinery

Noise would give rise to incorrect filtering frequency-band selection in signal filtering-based methods including fast kurtogram, teager energy operators and wavelet packet transform filters and meanwhile would result in incorrect selection of useful components and even mode mixing, end effects, etc., in signal decomposition-based methods including empirical mode decomposition, singular value decomposition and local mean decomposition. On the contrary, noise in stochastic resonance (SR) is beneficial to enhance weak signals of interest embedded in signals with strong background noise. Taking into account that nonlinear systems are crucial ingredients to activate the SR, here we investigate the SR in the cases of overdamped and underdamped harmonic-Gaussian double-well potential systems subjected to noise and a periodic signal. We derive and measure the analytic expression of the output signal-to-noise ratio (SNR) and the steady-state probability density (SPD) function under approximate adiabatic conditions. When the harmonic-Gaussian double-well potential loses its stability, we can observe the antiresonance phenomenon, whereas adding the damped factor into the overdamped system can change the stability of the harmonic-Gaussian double-well potential, resulting that the antiresonance behavior disappears in the underdamped system. Then, we use the overdamped and underdamped harmonic-Gaussian double-well potential SR to enhance weak useful characteristics for diagnosing incipient rotating machinery failures. Theoretical and experimental results show that adjusting both noise intensity and system parameters can activate overdamped and underdamped harmonic-Gaussian double-well potential SR in which there is a bell-shaped peak for the SNR. Additionally, the underdamped harmonic-Gaussian double-well potential SR is independent of frequency-shifted and rescaling transform to process large machine parameter signals and outperforms the overdamped one. Finally, comparing the advanced robust local mean decomposition (RLMD) method based on signal decomposition and the wavelet transform method based on noise cancellation or infogram method based on signal filtering, the overdamped or underdamped harmonic-Gaussian double-well potential SR methods characterize a better performance to detect a weak signal. Fault characteristics in the early stage of failures are successful in improving the incipient fault characteristic identification of rolling element bearings.

OTFT Biosensor on Flexible Substrates for Human Health Monitoring: a Review

With the development of the Internet of Things era, smart wearable devices have gradually entered people’s daily life, and these devices have provided great convenience to human beings in terms of real-time detection of human health and information transmission. Smart wearable electronic devices have also been gradually developed from smart bracelets, smart watches, and smart glasses into fibers or textiles. Organic thin-film transistor (OTFT) as a key component of flexible electronic devices has an important role in signal amplification, signal filtering, signal transmission, signal reception, and storage. In this article, we introduce the recent progress of OTFT based on 2-D film and 1-D fiber from the substrate of OTFT and focus on the preparation method and performance of OTFT based on 1-D fiber from the conductive fiber. In addition, some practical applications of OTFT sensors in human health detection are introduced. Index Electronic textiles, organic thin-film transistor (OTFT), smart wearables.

A Novel Smart Chair System for Posture Classification and Invisible ECG Monitoring.

In recent years, employment in sedentary occupations has continuously risen. Office workers are more prone to prolonged static sitting, spending 65−80% of work hours sitting, increasing risks for multiple health problems, including cardiovascular diseases and musculoskeletal disorders. These adverse health effects lead to decreased productivity, increased absenteeism and health care costs. However, lack of regulation targeting these issues has oftentimes left them unattended. This article proposes a smart chair system, with posture and electrocardiography (ECG) monitoring modules, using an “invisible” sensing approach, to optimize working conditions, without hindering everyday tasks. For posture classification, machine learning models were trained and tested with datasets composed by center of mass coordinates in the seat plane, computed from the weight measured by load cells fixed under the seat. Models were trained and evaluated in the classification of five and seven sitting positions, achieving high accuracy results for all five-class models (>97.4%), and good results for some seven-class models, particularly the best performing k-NN model (87.5%). For ECG monitoring, signals were acquired at the armrests covered with conductive nappa, connected to a single-lead sensor. Following signal filtering and segmentation, several outlier detection methods were applied to remove extremely noisy segments with mislabeled R-peaks, but only DBSCAN showed satisfactory results for the ECG segmentation performance (88.21%) and accuracy (90.50%).