Signal Stability Research Articles

System stability and signal enhancement with analyte protectants: Gas chromatography analysis of oxygenated-polycyclic aromatic hydrocarbons

Matrix effects can affect detection limits, precision, and accuracy and lead to signal enhancement or suppression effects in gas chromatography analysis. Analyte protectants, such as shikimic acid and gluconolactone, can imitate the effect of matrix components and reduce the differences in matrix effect between samples. This study aimed to investigate the ability of analyte protectants to enhance gas chromatography detector signals of different oxygenated-polycyclic aromatic hydrocarbons. Addition of 100 μg L−1 shikimic acid and 200 μg L−1 gluconolactone effectively enhanced detector response of the investigated target compounds. Addition of a higher content of analyte protectants did not result in any further enhancement. It was found that between four and eleven consecutive injections of a standard solution with analyte protectants were required to obtain a stable compound response. The long-term signal stability was then maintained with subsequent injections, though an overall negative drift of the system was observed over the sequence of 200 investigated injections. Analysis of the actual sample matrix instead of standards in pure solvent, as presented in this study, could also be a way to minimize the required number of injections. Shikimic acid and gluconolactone were first and foremost able to enhance signals of oxygenated-polycyclic aromatic hydrocarbons with similar functional groups (hydroxyl) in their molecular structure. It can be relevant to consider alternative analyte protectants with different functional groups according to the type of target compounds investigated.

Gold-Deposited Graphene Nanosheets for Self-Cleaning Graphene Surface-Enhanced Raman Spectroscopy with Superior Charge-Transfer Contribution.

The interaction of graphene with metals initiates charge-transfer interaction-induced chemical enhancements, which critically depend on the doping effect from deposited metallic configurations. In this paper, we have explored the gold nanoparticle-decorated monolayer graphene nanosheets for the large graphene-induced Raman enhancement of adsorbed analytes, indicating the surface-enhanced Raman spectroscopy (SERS) capabilities of metal-doped graphene (G-SERS). Here, the systematically sputtered Au thickness optimization procedure revealed noticeable modifications in the graphene Raman spectra and photoluminescence (PL) background quenching, which indicated favorable charge transfer through n-type doping of chemical vapor deposition-grown graphene nanosheets. The highly consistent, individually distributed morphology of the gold nanoislands over graphene nanosheets depicted a reproducibly uniform G-SERS signal with excellent relative standard deviation values (<5%), resulting in the strongest Raman intensity enhancement factors of ∼108 (MB) (methylene blue) and 107 (DPA) (2,6-pyridinedicarboxylic acid) composed of the weakest PL background. The combined charge-transfer-induced chemical enhancement and electromagnetic enhancement from individual Au nanoislands result in a lowering of detectability down to 10-16 M (MB) and 10-11 M (DPA) concentrations with efficient time-dependent signal stability. Additionally, the GAu demonstrated its effective (∼94.4%) photocatalytic degradation capabilities by decomposing MB dye molecules from a concentration of 1 μM to 2.52 fM within 60 min. Therefore, the prominent charge-transfer contribution through controlled Au decoration over graphene nanosheets provides a potential strategy for fabricating superior SERS sensors and photocatalysts exhibiting adequate signal consistency, stability, and photodegradation efficiency through overcoming the limitations of the traditional sensing platforms.

OptiMS: An Accessible Program for Automating Mass Spectrometry Parameter Optimization and Configuration.

Mass spectrometers have an enormous number of user-changeable parameters that drastically affect the observed mass spectrum. Using optimal parameters can significantly improve mass spectrometric data by increasing signal stability and signal-to-noise ratio, which decreases the limit of detection, thus revealing previously unobservable species. However, ascertaining optimal parameters is time-consuming, tedious, and made further challenging by the fact that parameters can act dependently on each other. Consequently, suboptimal parameters are frequently used during characterization, reducing the quality of results. OptiMS, an open-source, cross-platform program, was developed to simplify, accelerate, and more accurately determine optimal mass spectrometer parameters for a given system. It addresses common difficulties associated with existing software such as slow performance, high costs, and limited functionality. OptiMS efficacy was demonstrated through its application to multiple systems, quickly and successfully optimizing instrument parameters unassisted to maximize a user-defined metric, such as the intensity of a particular analyte. Additionally, among other features, OptiMS allows running of a sequence of predefined parameter configurations, reducing the workload of users wishing to obtain mass spectra under multiple sets of conditions.

Polydopamine-enhanced vertically-ordered mesoporous silica film anti-fouling electrochemical aptasensor for indicator-free Vibrio parahaemolyticus discrimination using stable inherent Au signal

Vertically-ordered mesoporous silica film (VMSF) has proven to be an effective anti-interference and anti-fouling layer in the field of analysis. However, because VMSF is not stable enough in complex samples, its application in sensing field is limited. We herein use mussel-inspired multi-functional agent polydopamine (PDA) to enhance the stability of VMSF on electrode. Owing to the amino-functionalized VMSF combined with amino groups on PDA, superhydrophilicity was achieved which was proved to enhance excellent anti-fouling property. In addition, the electrodeposition of Au nanoparticles (AuNP) in the nanochannel of VMSF serving as an internal electrochemical signal shows excellent electrochemical signal stability, which provides a prerequisite for maintaining the further detection accuracy in complex samples. Finally, we validated the detection performance of the anti-fouling sensing strategy using a foodborne pathogen, Vibrio parahaemolyticus (VP), as a model target. Specifically, the aptamer was modified by covalent bond on the PDA-integrated VMSF interface surface for the recognition of VP. Using shrimp homogenate as a real sample, the anti-fouling detection performance of the aptasensor was verified. The linear range of VP detection in real samples was 103-107 CFU/mL, and the detection limit was 103 CFU/mL. The results show that the anti-fouling aptasensor has excellent anti-interference and stability. It is worth emphasizing that this strategy (using inherent Au signal) enables rapid electrochemical analysis of VP without outer indicators, greatly reducing the difficulty of constructing an electrochemical VP detection strategy.

Biomimetic-Membrane-Protected Plasmonic Nanostructures as Dual-Modality Contrast Agents for Correlated Surface-Enhanced Raman Scattering and Photoacoustic Detection of Hidden Tumor Lesions.

Optical imaging and spectroscopic modalities are of considerable current interest for in vivo cancer detection and image-guided surgery, but the turbid or scattering nature of biomedical tissues has severely limited their abilities to detect buried or occluded tumor lesions. Here we report the development of a dual-modality plasmonic nanostructure based on colloidal gold nanostars (AuNSs) for simultaneous surface-enhanced Raman scattering (SERS) and photoacoustic (PA) detection of tumor phantoms embedded (hidden) in ex vivo animal tissues. By using red blood cell membranes as a naturally derived biomimetic coating, we show that this class of dual-modality contrast agents can provide both Raman spectroscopic and PA signals for the detection and differentiation of hidden solid tumors with greatly improved depths of tissue penetration. Compared to previous polymer-coated AuNSs, the biomimetic coatings are also able to minimize protein adsorption and cellular uptake when exposed to human plasma without compromising their SERS or PA signals. We further show that tumor-targeting peptides (such as cyclic RGD) can be noncovalently inserted for targeting the ανβ3-integrin receptors expressed on metastatic cancer cells and tracked via both SERS and PA imaging (PAI). Finally, we demonstrate image-guided resections of tumor-mimicking phantoms comprising metastatic tumor cells buried under layers of skin and fat tissues (6 mm in thickness). Specifically, PAI was used to determine the precise tumor location, while SERS spectroscopic signals were used for tumor identification and differentiation. This work opens the possibility of using these biomimetic dual-modality nanoparticles with superior signal and biological stability for intraoperative cancer detection and resection.

Supercapacitor‐based coordinated synthetic inertia scheme for voltage source converter‐based HVDC integrated offshore wind farm

AbstractA supercapacitor‐based coordinated synthetic inertia (SCSI) scheme for a voltage source converter‐based HVDC (VSC‐HVDC)‐integrated offshore wind farm (OWF) is proposed. The proposed SCSI allows the OWF to provide a designated inertial response to an onshore grid. Under the SCSI scheme, a supercapacitor is added to the DC side of each wind turbine generator via a bidirectional DC/DC converter, varying its voltage along with the offshore frequency to synthesise the desired inertial response. The HVDC grid side VSC employs a DC voltage/frequency droop control to convey the onshore frequency information to DC voltage without communication. Meanwhile, the wind farm side VSC regulates the offshore frequency to couple with the conveyed onshore frequency, considering voltage drop across the DC cables. An offshore frequency switching algorithm is incorporated to avoid undesired SCSI maloperation under offshore faults. The key parameters of the proposed SCSI are optimised through a small signal stability analysis. The effectiveness of the SCSI scheme is evaluated using a modified IEEE 39‐bus test system. The results show that the proposed SCSI scheme can provide required inertial support from WTG‐installed supercapacitors to the onshore grid through the VSC‐HVDC link, significantly improving the onshore frequency stability.

Optical bleaching and thermal stability of ESR signals in fault-related carbonates

Recrystallized carbonates formed on fault surfaces via fault activity and calcite veins in fault zones are promising dating materials for geochronological studies using methods such as electron spin resonance (ESR) dating. However, the bleaching characteristics and thermal stability of ESR signals in these materials have not been previously reported. In this study, three carbonates associated with fault activity (recrystallized carbonate, calcite vein, carbonate bedrock) were collected to investigate their bleaching characteristics and thermal behavior. The results of bleaching experiments show that the bleaching characteristics exhibit two patterns. Of seven observed signals, four were completely bleached by sun-like light exposure (g = 2.0040, g = 1.9995, g = 2.0057, g = 2.0018) in order of decreasing sensitivity to light. The other three signals (g = 2.0006, g = 2.0022, g = 2.0031) could not be fully zeroed, and their signal intensities reached stable residual values after different exposure times depending on the signal. The results of thermal annealing experiments show that the observed signals intensities decreased in the three samples during annealing, except the g = 2.0057 line. The g = 2.0006 line is the most promising for ESR dating on account of its stable thermal behavior and low sensitivity to optical bleaching. Lastly, the g = 2.0040 signal shows thermal instability, and caution is required when using this signal for dating.

Rapid Biodistribution of Fluorescent Outer-Membrane Vesicles from the Intestine to Distant Organs via the Blood in Mice.

A cell's ability to secrete extracellular vesicles (EVs) for communication is present in all three domains of life. Notably, Gram-negative bacteria produce a specific type of EVs called outer membrane vesicles (OMVs). We previously observed the presence of OMVs in human blood, which could represent a means of communication from the microbiota to the host. Here, in order to investigate the possible translocation of OMVs from the intestine to other organs, the mouse was used as an animal model after OMVs administration. To achieve this, we first optimized the signal of OMVs containing the fluorescent protein miRFP713 associated with the outer membrane anchoring peptide OmpA by adding biliverdin, a fluorescence cofactor, to the cultures. The miRFP713-expressing OMVs produced in E. coli REL606 strain were then characterized according to their diameter and protein composition. Native- and miRFP713-expressing OMVs were found to produce homogenous populations of vesicles. Finally, in vivo and ex vivo fluorescence imaging was used to monitor the distribution of miRFP713-OMVs in mice in various organs whether by intravenous injection or oral gavage. The relative stability of the fluorescence signals up to 3 days post-injection/gavage paves the way to future studies investigating the OMV-based communication established between the different microbiotas and their host.

Activity-Independent Enzyme-Powered Amplification for Improving Signal Stability and Fidelity in Biosensing.

Enzymes are an important tool used for signal amplification in biosensing. However, traditional amplification methods based on enzymes are always dependent on their catalytic activities, so their signals fluctuate with the change of microenvironment (e.g., pH and temperature). In this work, we communicate an activity-independent enzyme-powered (AIEP) amplification strategy for biosensing to improve signal stability and fidelity. To verify this hypothesis, the monitoring of oxidative stress during drug-induced liver injury was carried out. Carboxylesterase (CEs), highly expressed in hepatic tissue, was selected as the amplification tool. A CEs configuration-matching fluorophore (CMF) was designed and screened, and a nanobeacon was fabricated by loading CMF within an O2 •--responsive polymeric micelle. Since the degradation of the nanobeacon was triggered by O2 •-, CMF was released to bind with CEs, and the fluorescence was lit by CEs-CMF configuration matching but not catalytic reaction. Results demonstrated that the oxidative stress during drug-induced liver injury could be successfully monitored, and the hepatoprotective effects of repair drugs could be evaluated by cell and in vivo imaging. This strategy is flexible for bioactive molecules by altering the responsive unit and generally accessible for pharmacological evaluation.

Research on power system small signal stability analysis and correction based on LightGBM algorithm

Research on power system small signal stability analysis and correction based on LightGBM algorithm

Modelling and small signal stability for islanded microgrids with hybrid grid-forming sources based on converters and synchronous machines

Grid-forming (GFM) technologies based on converters or synchronous machines (SMs) were proposed as emerging approaches for improving inertia, damping, and strength of power girds with increasing renewable energy penetration. Although the stability of GFM converters has been widely studied, the dynamics of a grid-connected generator can be dictated by the bulk power systems. Therefore, the stability of islanded microgrids with hybrid GFM sources should be investigated. To fulfill this gap, this paper adopts a general component connection method for modelling islanded microgrids integrated with multiple generators, and models for SMs, grid-following (GFL) and GFM converters are developed. Additionally, a new GFM technology known as the motor-generator pair (MGP) is investigated, and the model for small signal analysis is derived. Then, full-order state-space models for nine scenarios with hybrid GFM sources as well as simulation models which are used to verify their effectiveness are built. Finally, small-signal dynamics of different scenarios are fully examined. In the scenarios with SMs integrated, the range of oscillation frequency is wider than all converter-based scenarios, and mechanical dynamics can dominate stability; and in scenarios with only GFM converters, though the damping can be improved compared to GFL converters, low frequency oscillation may occur, and the dominant factor changes from the phase locked loop and power controller to voltage controller; then improvement in damping can be observed in MGP-based scenarios, but roots that dominate stability are sensitive to current controller and excitation. Further, critical ranges for control parameters, GFM converter penetration and electrical distance in different scenarios are investigated.

Probabilistic Small Signal Stability Analysis with Wind Power Based on Maximum Entropy Theory

The probability parameters for the small signal stability in a system are studied to quantify the impact of uncertain wind power on system stability. With the increase in the scale of wind power access systems, how to more efficiently and accurately obtain the probability of small signal stability is worthy of further investigation. Therefore, this work proposes an analysis method of probabilistic small signal stability (PSSS) based on maximum entropy (ME) theory for studying power systems with uncertain wind power from doubly fed induction generators (DFIGs). Firstly, the sensitivity of the eigenvalues to the variable power is obtained by linearization. Then, when the probability characteristic for wind is known, the probability characteristic for the system critical eigenvalues is approximated using the ME method and the derived sensitivity. The proposed ME method is used in the analysis of the PSSS for power systems with different wind power penetration scales in case studies. Compared to the probability function for the eigenvalue obtained by the conventional series expansion method, the proposed method has excellent accuracy and sufficient efficiency in analysing the PSSS for a system with uncertain wind power.

Hardware and Software Design and Implementation of Surface-EMG-Based Gesture Recognition and Control System

The continuous advancement of electronic technology has led to the gradual integration of automated intelligent devices into various aspects of human life. Motion gesture-based human–computer interaction systems offer abundant information, user-friendly functionalities, and visual cues. Surface electromyography (sEMG) signals enable the decoding of muscle movements, facilitating the realization of corresponding control functions. Considering the inherent instability and minuscule nature of sEMG signals, this thesis proposes the integration of a dynamic time regularization algorithm to enhance gesture recognition detection accuracy and real-time system performance. The application of the dynamic time warping algorithm allows the fusion of three sEMG signals, enabling for the calculation of similarity between the sample and the model. This process facilitates gesture recognition and ensures effective communication between individuals and the 3D printed prosthesis. Utilizing this algorithm, the best feature model was generated by amalgamating six types of gesture classification model. A total of 600 training and evaluation experiments were performed, with each movement recognized 100 times. The experimental tests demonstrate that the accuracy of gesture recognition and prosthetic limb control using the temporal dynamic regularization algorithm achieves an impressive 93.75%, surpassing the performance of the traditional threshold control switch.

Mesoporous Silica-Layered Gold Nanorod Core@Silver Shell Nanostructures for Intracellular SERS Imaging and Phototherapy.

Precision diagnosis-guided efficient treatment is crucial to extending the lives of cancer patients. The integration of surface-enhanced Raman scattering (SERS) imaging and phototherapy into a single nanoplatform has been considered a more accurate diagnosis and treatment strategy for cancer nanotheranostics. Herein, we constructed a new type of mesoporous silica-layered gold nanorod core@silver shell nanostructures loaded with methylene blue (GNR@Ag@mSiO2-MB) as a multifunctional nanotheranostic agent for intracellular SERS imaging and phototherapy. The synthesized GNR@Ag@mSiO2-MB nanostructures possessed a uniform core-shell structure, strong near-infrared (NIR) absorbance, photothermal conversion efficiency (65%), dye loading ability, SERS signal, and Raman stability under phototherapy conditions. Under single 785 nm NIR laser irradiation, the intracellular GNR@Ag@mSiO2-MB nanostructures were dramatically decreased to <9%, which showed excellent photothermal and photodynamic effects toward cancer cell killing, indicating that the combination of photothermal therapy (PTT) and photodynamic therapy (PDT) of the GNR@Ag@mSiO2-MB nanostructures could greatly enhance the therapeutic efficacy of cancer cell death. GNR@Ag@mSiO2-MB nanostructures demonstrated a strong Raman signal at 450 and 502 cm-1, corresponding to the δ(C-N-C) mode, suggesting that the Raman bands of GNR@Ag@mSiO2-MB nanostructures were more efficient to detect CT-26 cell SERS imaging with high specificity. Our results indicate that GNR@Ag@mSiO2-MB nanostructures offer an excellent multifunctional nanotheranostic platform for SERS imaging and synergistic anticancer phototherapy in the future.

Design and experiment of high-field asymmetric waveform ion mobility spectrometry chip based on an integrated temperature control printed circuit board structure.

During the detection of volatile organic compounds (VOC) using high-field asymmetric waveform ion mobility spectrometry (FAIMS), the ambient temperature significantly impacts the accuracy of planar FAIMS. To mitigate the influence of ambient temperature on detection accuracy and enhance resolution, a FAIMS system based on the inner impedance characteristics of a printed circuit board (PCB) was designed for temperature control. This study, conducted under standard atmospheric pressure, aimed to assess the signal stability of a planar FAIMS instrument with and without temperature control, and the effect of temperature change on the detection ability of acetone, ethanol, and their mixture was studied using PCB self-heating. Experimental results demonstrated that the base noise in FAIMS with temperature control was 0.2pA, whereas that in FAIMS without temperature control was 1.8pA. Notably, with increasing temperature, the detection ability of FAIMS changes accordingly. The optimal relative detection ability of acetone was observed when the electrode plate was heated to 45°C under an electric field of 15 kV/cm. This study provides a novel approach to improve the resolving power of FAIMS systems and their signal-to-noise ratio. The utilization of a PCB-based temperature control proved effective in stabilizing FAIMS signal characteristics and optimizing detection capabilities, particularly for VOCs such as acetone. These findings have significant implications for improving the accuracy and resolving power of FAIMS systems in VOC detection applications.

Real-time validation of RoCoF – Enhancing advanced coordinated control strategy for voltage unbalance mitigation implementing demand side management

The absence of rotational masses in converter-interfaced microgrids has led to a reduction in system inertia. As a consequence, the stability of modern microgrids is at risk, especially in the case of unbalanced systems, resulting in significant issues such as an increase in the rate of change of frequency (RoCoF), disturbances in the nominal frequency, and unfavourable voltage unbalances. This research article introduces an advanced concept centered around a virtual synchronous generator designed to enhance RoCoF performance. This is achieved through the implementation of a positive and a negative (PN) - sequence controller scheme in coordination with demand side management to ensure that RoCoF remains within the limit of 2 Hz/s according to IEEE Standard 1547–2018 and the voltage unbalance factor (VUF) adheres to the established standard of 2 % according to IEC 61,000–3–13. The behaviour of the proposed control strategy during transient conditions has also been demonstrated. The framework of the virtual synchronous generator is utilized in this paper to demonstrate the influence of damping coefficient and moment of inertia on the low inertia system's frequency and transient response where it has been established that greater inertia and damping are essential for their enhancement. The study also conducts a small signal stability analysis to assess the effects of various parameters on system stability. Furthermore, the real-time efficacy of the coordinated control methodology based on virtual inertia has been experimentally verified using OPAL-RT simulator. The simulation and experimental results, both provide evidence of the successful performance of the proposed approach in realizing efficient RoCoF enhancement and VUF mitigation.

Towards a Miniaturized Photoacoustic Sensor for Transcutaneous CO2 Monitoring.

A photoacoustic sensor system (PAS) intended for carbon dioxide (CO2) blood gas detection is presented. The development focuses on a photoacoustic (PA) sensor based on the so-called two-chamber principle, i.e., comprising a measuring cell and a detection chamber. The aim is the reliable continuous monitoring of transcutaneous CO2 values, which is very important, for example, in intensive care unit patient monitoring. An infrared light-emitting diode (LED) with an emission peak wavelength at 4.3 µm was used as a light source. A micro-electro-mechanical system (MEMS) microphone and the target gas CO2 are inside a hermetically sealed detection chamber for selective target gas detection. Based on conducted simulations and measurement results in a laboratory setup, a miniaturized PA CO2 sensor with an absorption path length of 2.0 mm and a diameter of 3.0 mm was developed for the investigation of cross-sensitivities, detection limit, and signal stability and was compared to a commercial infrared CO2 sensor with a similar measurement range. The achieved detection limit of the presented PA CO2 sensor during laboratory tests is 1 vol. % CO2. Compared to the commercial sensor, our PA sensor showed less influences of humidity and oxygen on the detected signal and a faster response and recovery time. Finally, the developed sensor system was fixed to the skin of a test person, and an arterialization time of 181 min could be determined.

High-speed rail defect detection using multi-frequency exciting 3D ACFM

High load wheel-rail friction leads to surface defects on the rail, which requires an accuracy non-destructive testing (NDT) technology to prevent rail fracture and even major safety accidents. Alternating current field measurement (ACFM) has attracted attention due to its high detection precision and low sensitivity of lift-off and velocity effects. The paper proposes a multi-frequency, three-dimensional (3D) ACFM detection system that can obtain abundant detection information for multi-frequency comprehensive evaluation to improve detection accuracy. The system mainly includes an expandable phase-locked amplifier module and an adjustable multi-frequency signal source module, which provides a hardware IQ demodulation acceleration platform for multi-frequency and multi-channel ACFM detection to obtain enough defect signals for analysis. Analysis of the speed effect indicates that increasing the excitation frequency can improve the stability of the detection signal. We design a quantitative evaluation model for defects with a depth of 2–8 mm and surface angle between 30° and 75°.

Abstract IA020: Micronuclei are a nexus of DNA damage signaling and genomic instability

Abstract Micronuclei have classically been considered inert biomarkers of genomic instability arising from failed DNA damage repair and chromosome segregation errors in mitosis. Work from several groups including our own have now demonstrated that micronuclei are active contributors to the cellular response to DNA damage by driving chromothripsis and through induction of anti-viral gene expression programs mediated by the cGAS-STING pathway. We now show that the specific DNA damage type leading to micronuclei formation influences the capacity for cGAS localization and activation. This arises in part due to discrete chromatin features, present prior to DNA damage induction, that are retained in micronuclei several days after their formation. Together these data demonstrate that micronuclei connect the pre-damage chromatin status and the chromatin context of micronuclei-inciting lesions to the long-term signaling outcomes important for anti-tumor immunity. This finding implies that micronuclei represent archives for the nature of DNA repair failure and downstream signaling consequences. Based on this premise we will present our efforts in micronuclear proteomics where we uncover common features of micronuclei including splicing deficiencies. Such deficiencies presage exacerbated MN-associated DNA damage that is upstream of chromothripsis. These studies have direct implications for how cells sense the aftermath of DNA damage and how micronuclei contribute to ongoing genomic instability. Citation Format: Shane M. Harding. Micronuclei are a nexus of DNA damage signaling and genomic instability [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr IA020.

Adaptive Normalization and Feature Extraction for Electrodermal Activity Analysis

Electrodermal Activity (EDA) has shown great potential for emotion recognition and the early detection of physiological anomalies associated with stress. However, its non-stationary nature limits the capability of current analytical and detection techniques, which are highly dependent on signal stability and controlled environmental conditions. This paper proposes a framework for EDA normalization based on the exponential moving average (EMA) with outlier removal applicable to non-stationary heteroscedastic signals and a novel set of features for analysis. The normalized time series preserves the morphological and statistical properties after transformation. Meanwhile, the proposed features expand on typical time-domain EDA features and profit from the resulting normalized signal properties. Parameter selection and validation were performed using two different EDA databases on stress assessment, accomplishing trend preservation using windows between 5 and 20 s. The proposed normalization and feature extraction framework for EDA analysis showed promising results for the identification of noisy, relaxed and arousal-like patterns in data with conventional clustering approaches like K-means over the aforementioned normalized features.