An objective, principal-component-analysis (PCA) based, method which improves the quartz-crystal-microbalance (QCM) sensing performance

Corradi, Elena; Agostini, Matteo; Greco, Gina; Massidda, Davide; Santi, Melissa; Calderisi, Marco; Signore, Giovanni; Cecchini, Marco

doi:10.1016/j.sna.2020.112323

Cited by 11 publications

(3 citation statements)

References 17 publications

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“…Analytical merits including limits of detection, standard deviation, and working range are important components for a diagnosis work, and the analyses must be properly performed to ensure results are reproducible among labs (Urban 2020). Methodology development can be strengthened by statistical analysis terms of total variance, PCA (Corradi et al, 2020) and PLS (Henao-Escobar et al, 2015) when applied to demonstrate specific detection of target biomolecular analytes.…”

Section: Data Processingmentioning

confidence: 99%

Grand Challenges and Perspectives in Biomedical Analysis and Diagnostics

Cheng

2021

Front. Anal. Sci.

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Section: Data Processingmentioning

confidence: 99%

Grand Challenges and Perspectives in Biomedical Analysis and Diagnostics

Cheng

2021

Front. Anal. Sci.

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“…KL conversion is similar in concept to principal component analysis (PCA) which is used to extract the features of two-dimensional image data with the average values of the target image. Recently, the PCA data-processing technique has been employed for biosensing data analyses to obtain vector quantization [ 21 , 22 , 23 , 24 ], and its high feature extraction ability has been demonstrated. Therefore, a similar effect is expected even if KL conversion is based on the same principle.…”

Section: Introductionmentioning

confidence: 99%

Data Processing of SPR Curve Data to Maximize the Extraction of Changes in Electrochemical SPR Measurements

et al. 2022

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We developed a novel measuring and data-processing method for performing electrochemical surface plasmon resonance (EC-SPR) on sensor surfaces for which detecting a specific SPR angle is difficult, such as a polymer having a non-uniform thickness with coloration. SPR measurements are used in medicine and basic research as an analytical method capable of molecular detection without labeling. However, SPR is not good for detecting small molecules with small refractive index changes. The proposed EC-SPR, which combines SPR measurements with an electrochemical reaction, makes it possible to measure small molecules without increasing the number of measurement steps. A drawback of EC-SPR is that it is difficult to detect a specific SPR angle on electron mediators, and it was found that it may not be possible to capture all the features produced. The novel method we describe here is different from the conventional one in which a specific SPR angle is obtained from an SPR curve; rather, it processes the SPR curve itself and can efficiently aggregate the feature displacements in the SPR curves that are dispersed through multiple angles. As an application, we used our method to detect small concentrations of H2O2 (LOD 0.7 μM) and glutamate (LOD 5 μM).

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“…PCA is based on the dimensional reduction of a large dataset to highlight its most statistically significant components, which ideally are related to the signals of interest, while removing the less significant components, which could be associated with frequency instability. Lately, Corradi et al applied the PCA method to improve the detection limit of a QCM sensor operating in multiple overtones [ 25 ]. Mumyakmaz et al combined PCA with neural networks to compensate for the effect of humidity in toluene gas monitoring [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Method for Improving Stability of Monolithic Quartz Crystal Microbalance Operating under Harsh Environmental Conditions

Fernandez

Calero

Jiménez

et al. 2021

Sensors

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Monolithic quartz crystal microbalance (MQCM) has recently emerged as a very promising technology suitable for biosensing applications. These devices consist of an array of miniaturized QCM sensors integrated within the same quartz substrate capable of detecting multiple target analytes simultaneously. Their relevant benefits include high throughput, low cost per sensor unit, low sample/reagent consumption and fast sensing response. Despite the great potential of MQCM, unwanted environmental factors (e.g., temperature, humidity, vibrations, or pressure) and perturbations intrinsic to the sensor setup (e.g., mechanical stress exerted by the measurement cell or electronic noise of the characterization system) can affect sensor stability, masking the signal of interest and degrading the limit of detection (LoD). Here, we present a method based on the discrete wavelet transform (DWT) to improve the stability of the resonance frequency and dissipation signals in real time. The method takes advantage of the similarity among the noise patterns of the resonators integrated in an MQCM device to mitigate disturbing factors that impact on sensor response. Performance of the method is validated by studying the adsorption of proteins (neutravidin and biotinylated albumin) under external controlled factors (temperature and pressure/flow rate) that simulate unwanted disturbances.

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An objective, principal-component-analysis (PCA) based, method which improves the quartz-crystal-microbalance (QCM) sensing performance

Cited by 11 publications

References 17 publications

Grand Challenges and Perspectives in Biomedical Analysis and Diagnostics

Grand Challenges and Perspectives in Biomedical Analysis and Diagnostics

Data Processing of SPR Curve Data to Maximize the Extraction of Changes in Electrochemical SPR Measurements

A Real-Time Method for Improving Stability of Monolithic Quartz Crystal Microbalance Operating under Harsh Environmental Conditions

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