Signal Drift Research Articles

Jellyfish‐Inspired High‐Sensitivity Pressure‐Temperature Sensor

AbstractIn recent years, biomimetic high‐sensitivity tactile sensors increasingly become a research focus. Specifically, hydrogel tactile sensors based on ionic‐electronic mechanisms gain widespread attention due to their excellent pressure sensitivity. However, due to the saturation deformation of sensitive elements, these sensors struggle to accurately measure pressure under high‐pressure conditions. Additionally, as hydrogels cause signal drift under constant pressure and ionic‐electronic mechanisms are susceptible to temperature interference, these characteristics limit their application. Inspired by the jellyfish's “mesoglea” and “ectoderm” structures, a novel tactile sensor is developed that combines the ionic‐electronic mechanism with a filling structure. This sensor integrates the hydrogel with a flexible framework to create a jellyfish‐like umbrella structure. This design achieves extremely high pressure sensitivity and improves signal drift. By utilizing the different response characteristics of the capacitance and resistance values of a single sensing element to pressure and temperature changes, it enables simultaneous measurement of temperature and pressure, thereby enhancing its potential for application in wearable electronics and robotics.

An ASIC-based system-in-package MEMS gas sensor with impedance spectroscopy readout and AI-enabled identification capabilities

The main advantages of micromachined metal oxide semiconductor (MOX) gas sensors, in particular their low cost, high sensitivity, miniaturization and low power consumption, are compromised by lack of selectivity and long-term sensor signal drifts, which often hinder their application in real-world sensing applications. To increase the sensor data dimensionality, temperature cycled operation (TCO) and impedance spectroscopy (IS) readout was proposed, enabling the acquisition of large datasets from a single sensor, as suitable to be exploited by machine learning techniques. Furthermore, recent studies have shown how the IS readout minimizes the issues represented by the sensor long-term signal drift.The aim of this work is the development of a smart system-in-package, integrating a state-of-the-art micromachined MOX gas sensor based on a wafer-level nanostructured sensing layer with a novel versatile sensor interface chip, capable of high performance IS readout. We propose a miniaturized sensing device, which is a small, lightweight low power consumption chemical sensing micro-system with fast and accurate classification capabilities, suitable to be deployed in long multi-node sensing cables or on unmanned aerial vehicles. A software suite comprising a sensor training wizard was also developed, enabling users with no technical background to train the sensing system.

Saline based microfluidic soft pressure sensor utilizing a three-dimensional focused electric field for motion and healthcare monitoring

This paper introduces the ‘Spatially Focused Saline-based Pressure Sensor (SF-SaPS)', a novel soft microfluidic pressure sensor featuring a distinctive three-dimensional focusing structure. By critically reducing the cross-sectional area of the microchannel at the focused structure, the SF-SaPS achieves excellent sensitivity to pressure within the sensing region. With the spatially focused region, the SF-SaPS could detect a wide range of pressure from gentle touches to human weight, which is typically unachievable with low-conductivity sensing media such as saline, a medium inherently safe for human use. Beyond its sensitivity, the SF-SaPS exhibits sensing performance and stability comparable with conventional liquid metal-based pressure sensors. Our sensor demonstrated minimal signal drift, a rapid response time of 70 ms under cyclic loading, and 20-day long-term stability tests immersed in water. Additionally, the sensor possesses a transparency advantage unattainable by liquid metal sensors as we utilized transparent polymers and saline. A unique advantage of the SF-SaPS lies in its selective spatial and mechanical sensitivity; as the electrical resistance is highly dependent on changes in the cross-sectional area of the microchannels, the sensor has superior pressure sensitivity compared to bending and strain. Finally, various application examples highlight the SF-SaPS's advantages. By configuring the sensor in a two-axis array, the SF-SaPS facilitates pressure mapping across a plane. Additionally, it proves effective in healthcare monitoring, from radial pulse to finger movements. In conclusion, the SF-SaPS's combination of performance, stability, biocompatibility, and transparency positions this sensor as a versatile tool for applications extending beyond healthcare, as demonstrated in this study.

Fundamental Investigation of Signal Drift in Continuous Liquid Chromatography/High Resolution Mass Spectrometric Plasma Analysis Toward Global Metabolomics

Fundamental Investigation of Signal Drift in Continuous Liquid Chromatography/High Resolution Mass Spectrometric Plasma Analysis Toward Global Metabolomics

Inferring the Accurate Locations of Noise Records in Mobile Phone Location Data

ABSTRACTThe positioning uncertainty of mobile phone location (MPL) data greatly influences location services and crowd behavior analysis. Although many achievements have been made in controlling its main sources (signal drift and ping‐pong effects), several problems, such as single‐oscillation patterns, insufficient position optimization, and a lack of effective evaluation, remain. In this study, a set of MPL data quality optimization methods are proposed. First, the characteristics of drift records and the oscillation patterns of ping‐pong records are discussed. The quality of the MPL data is subsequently controlled with the proposed feature‐based drift‐record detection method, complex oscillation pattern‐based ping‐pong‐record detection method, and cumulative duration weighting‐based ping‐pong‐record optimization method. These methods are applied to the MPL dataset of a major operator in Nanjing city, and the optimization effect is evaluated with GPS data collected synchronously. The results show that the proposed detection and optimization methods can effectively improve the accuracy of MPL data.

Measurement of Oscillatory and Dissipative Resonator Characteristics of Solid-State Wave Gyroscopes: Algorithms for Operational Correction of Systematic Signal Drift

The article discusses the possibilities of increasing the output signal accuracy of integrating solid-state wave gyroscopes manufactured with a reduction in the requirements for the residual characteristics of the multi-frequency and multi-factor ratios of their resonators, as well as for the centering of the control ring electrode. These capabilities involve the use of a more complex output function that includes an additional part due to the effect of these errors on the systematic drift function. However, its formation requires introduction of an interval shutdown of the parametric excitation system so as to increase the purity of identification of the listed factors. To reveal this topic, the following is sequentially described: mathematical formulation of the problem; general analysis of the systematic drift of the integrating gyroscope signal caused by mechanical errors in the design of its resonator; autonomous algorithmic reduction of the influence of the dominant residual differentials in the mode of interval disconnection of excitation; autonomous algorithmic reduction of the influence of the dominant residual frequency difference in the mode of interval disconnection of excitation; simultaneous algorithmic compensation of the influence of residual Q and Frequency in the interval disconnection mode of excitation; estimation of the signal drift component of the integrating gyroscope, due to errors in the control loops, as well as the possibility of its reduction. The analysis of these problems is carried out on the basis of a model of wave processes in the gyroscope resonator, obtained only on the basis of the laws of classical mechanics. There were no additional errors due to the imperfection of the electrical circuits for processing measurement and control signals. Various computational schemes discussed in the article can also be useful for performing operational adjustments of the gyroscope measurement system, which may be required as a result of the design aging factor, as well as after its intensive use in a wide range of external disturbances.

Humidity-independent NO2 gas sensors based on ZnO-NiOFx nanocomposites and the synergistic humidity-immune effect of fluorine doped NiO

Clean, alternative energy sources, especially fuel cells, are gradually attracting global attentions while the produced toxic nitrogen dioxide (NO2) is a greatly hazardous chemical impacting their energy efficiencies. Metal oxide semiconductors (MOS) hold significant promise as NO2 sensors. However, intensive humidity interaction intensifies signal drifts and reliable response inhibitions under variable humidity conditions. In this study, we present a novel approach to address this issue by engineering in-situ F-doped NiO nanocomposites (NiOFx) decorated on ZnO snowflakes achieved through decomposition modulation of ZnOHF precursors. The optimized NO2 sensor demonstrates unparalleled humidity-independence across a wide operating temperature range with prime sensitivity, low detection limit and rapid response/recovery. Matrix algorithm is also implemented in highly precise NO2 identification under complicated atmospheric and humid conditions. Mechanism studies based on temperature programmed desorption (TPD), quasi in-situ X-ray photoelectron spectroscopy (Quasi in-situ XPS) reveal that F− dopants facilitate interfacial electron transferring and inhibit oxygen activity. In-situ diffuse reflectance infrared Fourier transform spectroscopy (In-situ DRIFTS) demonstrates that hygroscopic NiO and electronegative F− synergistically obstruct hydroxyl adsorptions on sensing materials. The innovative approach offers a promising solution for enhancing moisture resistance of MOS sensors for real-time NO2 concentration monitoring in fuel cells and provides valuable insights into anti-humidity mechanisms.

Physically stressed bees expect less reward in an active choice judgement bias test.

Emotion-like states in animals are commonly assessed using judgment bias tests that measure judgements of ambiguous cues. Some studies have used these tests to argue for emotion-like states in insects. However, most of these results could have other explanations, including changes in motivation and attention. To control for these explanations, we developed a novel judgment bias test, requiring bumblebees to make an active choice indicating their interpretation of ambiguous stimuli. Bumblebees were trained to associate high or low rewards, in two different reward chambers, with distinct colours. We subsequently presented bees with ambiguous colours between the two learnt colours. In response, physically stressed bees were less likely than control bees to enter the reward chamber associated with high reward. Signal detection and drift diffusion models showed that stressed bees were more likely to choose low reward locations in response to ambiguous cues. The signal detection model further showed that the behaviour of stressed bees was explained by a reduction in the estimated probability of high rewards. We thus provide strong evidence for judgement biases in bees and suggest that their stress-induced behaviour is explained by reduced expectation of higher rewards, as expected for a pessimistic judgement bias.

Assessing the Precision and Accuracy of Foraminifera Elemental Analysis at Low Ratios

AbstractThe minor and trace element compositions of biogenic carbonates such as foraminifera are important tools in paleoceanography research. However, most studies have focused primarily on samples with element to calcium (El/Ca) ratios higher than the El/Ca range often found in benthic foraminifera. Here, we systematically assess the precision and accuracy of foraminifera elemental analysis across a wide range of El/Ca especially at relatively low ratios, using a method on a Thermo Scientific iCAP Qc quadrupole Inductively Coupled Plasma Mass Spectrometer (ICP‐MS). We focus on two benthic foraminifera species, Hoeglundina elegans and Cibicidoides pachyderma, and prepared a suite of solution standards based on their typical El/Ca ranges to correct for signal drift and matrix effects during ICP‐MS analysis and to determine analytical precision. We observe comparable precisions with published studies at high El/Ca, and higher relative standard deviations for each element at lower El/Ca, as expected from counting statistics. The overall long‐term analytical precision (2σ) of the H. elegans‐like consistency standard solutions was 6.5%, 4.6%, 5.0%, for Li/Ca, Mg/Ca, Mg/Li, and 6.4%, 10.0%, 4.2% for B/Ca, Cd/Ca, Sr/Ca. The precision for H. elegans‐like Mg/Li is equivalent to a temperature uncertainty of 0.5–1.1°C. Measurement precisions were also assessed based on three international standards (one solution and two powder standards) and replicate measurements of H. elegans and C. pachyderma samples. We provide file templates and program scripts that can be used to design calibration and consistency standards, prepare run sequences, and convert the raw ICP‐MS data into molar ratios.

Qualitative and quantitative detection of camellia oil adulteration using electronic nose based on wavelet decomposition humidity correction

This study addresses the challenge of environmental humidity impacting the accuracy of metal oxide semiconductor (MOS)-based electronic nose systems in detecting adulterated camellia oil. A self-developed electronic nose platform with eight MOS sensors was used to detect adulteration in camellia oil mixed with varying ratios of rapeseed, soybean, and corn oils at different humidity levels (20%, 40%, and 60%). Wavelet decomposition using fourth-order Symlet wavelet was applied to correct response signals, mitigating humidity's effect on detection accuracy. Linear discriminant analysis (LDA), support vector machine (SVM), and random forest (RF) were employed to build qualitative identification models using pre- and post-correction datasets, while partial least squares regression (PLSR) and backpropagation neural network (BPNN) were used for quantitative prediction. Results showed that both qualitative and quantitative models significantly improved performance after correcting signal drift with wavelet decomposition. The qualitative model's 10-fold cross-validation prediction accuracy increased to 98.67% from 88.67%, while the quantitative model's average R2 reached 0.99 with RMSE reduced to 3.64 mL/100 mL, compared to pre-correction R2 of 0.86 and RMSE of 9.63 mL/100 mL. Notably, the RF and BPNN models outperformed others in qualitative and quantitative detection, respectively. These findings highlight the potential of electronic nose technology with humidity correction for authenticating camellia oil.

Eco-friendly electrochemical assay of oxytetracycline and flunixin in their veterinary injections and spiked milk samples

Two solid-contact electrochemical sensors were developed for detection of each of oxytetracycline HCl (OXY), and the co-formulated non-steroidal anti-inflammatory drug flunixin meglumine (FLU) in veterinary formulations and animal-derived food products. The designed sensors were based on a glassy carbon electrode as the substrate material and high molecular weight polyvinyl chloride (PVC) polymeric ion-sensing membranes doped with multiwalled carbon nanotubes (MWCNTs) to improve the potential stability and minimize signal drift. For determination of OXY, the sensing membrane was modified with potassium tetrakis (4-chlorophenyl) borate (K-TCPB), which was employed as a cation exchanger, and 2-hydroxypropyl-β-cyclodextrin (HP-ßCD), which was used as an ionophore. A linear response within a concentration range of 1 × 10− 6-1 × 10− 2 M with a slope of 59.47 mV/decade over a pH range of 1–5 was recorded. For the first time, two potentiometric electrodes were developed for determination of FLU, where the sensing membrane was modified with tetra dodecyl ammonium chloride (TDDAC) as an anion exchanger. A linear response within a concentration range of 1 × 10− 5-1 × 10− 2 M and a slope of -58.21 mV/decade over a pH range of 6–11 was observed. The suggested sensors were utilized for the selective determination of each drug in pure powder form, in veterinary formulations, and in spiked milk samples, with mean recoveries ranging from 98.50 to 102.10, and without any observed interference. The results acquired by the proposed sensors were statistically analyzed and compared with those acquired by the official methods, and the results showed no significant difference.Graphical

Calibration-free and ready-to-use wearable electroanalytical reporting system (r-WEAR) for long-term remote monitoring of electrolytes markers

A major bottleneck in the development of wearable ion-selective sensors is the inherent conditioning and calibration procedures at the user's end due to the signal's instability and non-uniformity. To address this challenge, we developed a strategy that integrates three interdependent materials and device engineering approaches to realize a Ready-to-use Wearable ElectroAnalytical Reporting system (r-WEAR) for reliable electrolytes monitoring. The strategy collectively utilized (1) finely-configured diffusion-limiting polymers to stabilize the electromotive force in the electrodes, (2) a uniform electrical induction in electrochemical cells to normalize the open-circuit potential (OCP), and (3) an electrical shunt to maintain the OCP across the entire sensor in the r-WEAR. The approaches jointly enable fabrication of homogeneously stable and uniform ion-selective sensors, eliminating common conditioning and calibration practices. As a result, the r-WEAR demonstrated a signal's variation down to ±1.99 mV with a signal drift of 0.5 % per hour (0.12 mV h−1) during a 12-h continuous measurement of 10 sensors and a signal drift as low as 13.3 μV h−1 during storage. On-body evaluations of the r-WEAR for four days without conditioning and re-/calibration further validated the sensor's performance in realistic settings, indicating its remarkable potential for practical usage in a user operation-free manner in wearable healthcare applications.

Pumpless microfluidic sweat sensing yarn

Textile sweat sensors possess immense potential for non-invasive health monitoring. Rapid in-situ sweat capture and prevention of its evaporation are crucial for accurate and stable real-time monitoring. Herein, we introduce a unidirectional, pump-free microfluidic sweat management system to tackle this challenge. A nanofiber sheath layer on micrometer-scale sensing filaments enables this pumpless microfluidic design. Utilizing the capillary effect of the nanofibers allows for the swift capture of sweat, while the differential configuration of the hydrophilic and hydrophobic properties of the sheath and core yarns prevents sweat evaporation. The Laplace pressure difference between the cross-scale fibers facilitates the management system to ultimately expulse sweat. This results in microfluidic control of sweat without the need for external forces, resulting in rapid (<5 s), sensitive (19.8 nA μM−1), and stable (with signal noise and drift suppression) sweat detection. This yarn sensor can be easily integrated into various fabrics, enabling the creation of health monitoring smart garments. The garments maintain good monitoring performance even after 20 washes. This work provides a solution for designing smart yarns for high-precision, stable, and non-invasive health monitoring.

High-speed bioimpedance-based gating system for radiotherapy: Prototype and proof of principle.

To investigate a novel bioimpedance-based respiratory gating system (BRGS) designed for external beam radiotherapy and to evaluate its technical characteristics in comparison with existing similar systems. The BRGS was tested on three healthy volunteers in free breathing and breath-hold patterns under laboratory conditions. Its parameters, including the time delay (TD) between the actual impedance change and the gating signal, temperature drift, root mean square (RMS) noise, and signal-to-noise ratio (SNR), were measured and analyzed. The gate-on TD and the gate-off TD were found to be 9.0±2.0ms [mean±standard deviation (M±SD)] and 7.2±1.3ms, respectively. The temperature drift of the BRGS output signal was 0.02 Ω after 30 min of operation. RMS noise averaged 0.14±0.05 Ω (M±SD) for all subjects and varied from 0.08 to 0.20 Ω with repeated measurements. A significant difference in SNR (p<0.001) was observed between subjects, ranging from 4 to 15. The evaluated bioimpedance-based gating system showed a high performance in real-time respiratory monitoring and may potentially be used as an external surrogate guidance for respiratory-gated external beam radiotherapy. Direct comparison with commercially available systems, 4D correlation studies, and expansion of the patient sample are goals for future preclinical studies.

Exploring the rich geometrical information in cosmic drift signals with covariant cosmography

Exploring the rich geometrical information in cosmic drift signals with covariant cosmography

Over-Time Stability Evaluation of Fluorinated Self-Assembled Monolayer on Commercial Indium Tin Oxide Electrode on PET Substrate

Motivation: Self-Assembled Monolayer (SAM) modified electrode has a key role in electrochemical biosensor applications to achieve desired sensing properties such as selective interaction with target protein and anti-fouling properties of non-specific protein. However, the degradation of SAM layer on the electrode can cause the electrochemical response to drift over time. This causes adversary effect on the designed biosensor such as limited shelf life and inconsistent electrochemical signal reading between electrodes. For that matter, it is important to understand the signal drift behaviour and ultimately obtain a SAM-modified electrode with good stability over time. In this study, we observed the signal drift of SAM-modified indium tin oxide electrode on PET substrate (ITO-PET). Three-electrode electrochemical impedance spectroscopy (EIS) measurement was carried to evaluate the electrochemical properties of the ITO-PET substrate over time. Materials and Methods: Commercial ITO-PET (Adafruit, NY, USA) was used as electrode and was modified using Perfluoro-octyltriethoxysilane (Sigma Aldrich, St. Louis, MO, USA) self-assembled monolayer. The ITO-PET substrate was modified by using room temperature RCA-1 silanization process as shown in Figure 1. The modified electrode was rinsed in ethanol and DI water and stored in dark condition with temperature of 5oC. The Electrochemical Impedance Spectroscopy measurements were carried by using Solartron SI1260 impedance analyser tandem with SI1287 potentiostat. with saturated KCl Ag/AgCl (RRPEAGCL2, Pine Research, NC, USA) electrode and Pt wire counter electrode (MW-1032; BASi, West Lafayette, IN, USA). Potassium Ferricyanide (K3Fe(CN)6) (Fischer Scientific, Fair Lawn, NJ, USA) with concentration of 10 mM in 1x PBS was used as redox probe. The EIS run was set at 0.31 Vdc and 10 mV Vac amplitude with frequency ranging from 0.1 – 10000 Hz. Results: We observed significant increase charge transfer resistance (Rct)increase of SAM-ITO sample (4498 ± 460 Ω.cm2) compared to the bare ITO sample (1348 ± 68 Ω.cm2). The signal also maintains its consistency after one week of storage in enclosed dry and dark environment at 5oC with 3% change in average Rct value (133 Ω.cm2). Ongoing work in this study includes the electrochemical signal evaluation of the ITO-SAM electrode exposed to protein such as casein and BSA. Figure 1

(Invited) Long-Term, in vivo Measurement of Biomarkers Using Molecular Switches

Biosensors that can detect specific analytes – continuously, in vivo, in real time – would offer exciting capabilities for fundamental research and clinical medicine. However, their development has proven difficult due to biofouling, probe degradation and signal drift that often occur in vivo. In nature, evolution has solved similar problems through the use of nanostructures. By drawing inspiration from nature, we have developed a synthetic biosensor that can continuously detect specific target molecules - continuously, in vivo, in real time – for prolonged periods. Specifically, our system is stable for more than one month in undiluted serum in vitro, and retains excellent stability for multiple days, even when implanted in the blood vessel of live rats. In this way, our work provides a generalizable design foundation for a new generation of biosensors that can continuously operate in vivo for extended durations.

(Invited) Tackling Leakage, Drift, and Variation in Printed Carbon Nanotube-Based Electronic Biosensors

Semiconducting carbon nanotubes (CNTs) have been pursued for use in electronic biosensors for decades. Their all-surface molecular structure, sizeable semiconducting bandgap, and solution-phase compatibility make them highly sensitive and versatile options for transducing target bioelectrical signals. However, amid the thousands of reports on CNT-based electronic biosensors, very little attention has been given to identifying (let alone addressing) the impact of leakage current, signal drift, and device-to-device variation. This talk will present recent results focused on tackling these issues with specific emphasis on printed CNT-based biosensors. For instance, a variety of passivation strategies were studied to determine the role of leakage current for CNT transistor-based biosensors (i.e., bioFETs or ion-sensitive FETs), revealing that a bilayer epoxy/high-k dielectric stack was most effective at minimizing unwanted leakage current. The influence of signal drift will also be demonstrated, likely playing a significant role in many previous reports of CNT-based biosensors characterized by sequential concentration spikes. Finally, strategies for addressing device-to-device variation in these biosensors will be discussed, including the motivation for a printed thin-film device rather than a single-CNT configuration. Two things seem certain about this field: 1) the promise of CNT-based biosensors continues to suggest they are worth ongoing pursuit, and 2) there is much work remaining towards achieving a reproducible, reliable electronic biosensing technology from CNTs.

Mimicking chirality floralform heterostructure: A multivariate metal-based nanoparticles with highly charge transformation interface and multivariate recognition

Enantioselective identification of chiral molecules holds immense significance in the fields of biological processes, chemical reactions, and drug development due to the optical rotation properties of enantiomers. Moreover, the chiral nanocomposite plays an important role in capable of selectively interacting with specific chiral molecules. By utilizing the chiral surfaces of metal polyphenol framework, an enantioselective identification chiral nanocomposite is fabricated on polyphenol colloidal spheres (PCS). The multivariate metal-based nanocomposite use L-tartaric acid (TA) and copper as a chiral recognition selector and signal corrector, aminothiophenol (PATP) anchoring Ag NPs as artificial traction skeleton. Applying L-/ D-cysteine as patterns enantiomers, the chiral recognition selector Cu- L-TA framework perform stereoselective recognition of target molecules through strong affinity and hydrogen interaction. The discriminative SERS signal and CT-related totally symmetric (a1) value of Cu- PCS@Ag NPs and PATP molecules is regarded as discriminating part and internal standard to correct the signal drifting. The put forward method has a good linearity in the concentration range of 1 nM ∼ 10 mM and detection limits as low as 0.37 pM and 0.30 pM for L/D-Cys. This work provides specific method for the chiral molecule recognition and determination in complex matrix sample.

Capillary-osmotic wearable patch based on lateral flow assay for sweat potassium analysis

This paper reports a simple, disposable, and wearable patch inspired by lateral flow assay (LFA) that can continuously and non-invasively sample sweat for colorimetric sensing of potassium (K+). K+ is an important biomarker for healthy cardiovascular and neuromuscular functions of the body. Current techniques for K+ sensing in sweat commonly use ion-selective electrodes that require complex fabrication steps, signal drift issues, and active perspiration for continuous operation. Here, the sensor uses passive osmotic-capillary principles to collect sweat from the skin without the need of external power for sampling. A skin-mounted hydrogel patch equilibrated with glucose and glycerin solutions can extract fluid from the skin at rest because of the high osmotic strength of the hydrogel compared to sweat. The gel delivers fluid to a commercial colorimetric assay via a paper strip. The assay contains the reagent dipicrylamine which is selective to K+. On-body human trials prove that these patches function with low sweat volumes (∼2–3 µL) and measure K+ concentration in sweat extracted both during exercise and rest. The sweat potassium concentration is independent of the sweat rate and its magnitude matches that of blood. Such economical patches could open opportunities for at-home or in-field point-of-care (POC) diagnostics.