On Employing a Savitzky-Golay Filtering Stage to Improve Performance of Spectrum Sensing in CR Applications Concerning VDSA Approach

Angrisani, L.; Capriglione, Domenico; Cerro, Gianni; Ferrigno, Luigi; Miele, Gianfranco

doi:10.1515/mms-2016-0019

Cited by 18 publications

(5 citation statements)

References 10 publications

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“…The proposed method replaces it with the SG filter on each ICA component [35]. In addition, Angrisani et al reported that the SG filter could increase the frequency perception of signals with low SNR more than the MA [47]. The order and window size of the SG filter are fourth and 25 units (SG_order = 4, frameLength = 25).…”

Section: E Proposed Ippg Methods On Non-facial Regionsmentioning

confidence: 99%

Robust Method for Non-Contact Vital Sign Measurement in Videos Acquired in Real-World Light Settings From Skin Less Affected by Blood Perfusion

Tangjui,

Taeprasartsit

2024

IEEE Access

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Color fluctuations caused by blood perfusion on the skin are an essential tool for the success of imaging photoplethysmography (iPPG) methods. However, color fluctuation of the non-facial skin is less observable than that of the facial skin. Furthermore, some light sources may produce image artifacts obscuring vital signs that iPPG methods are aimed to observe. This work contributes to an iPPG domain in several ways. First, it systematically visualizes and evaluates the impact of light settings on the accuracy of heart-rate estimation. Three light settings were arranged, and Eulerian video magnification was applied to illustrate their underlying characteristics. This work showed that fluorescent tubes could produce stripe artifacts and failed existing iPPG methods. Second, techniques to strengthen blood perfusion signals and better estimate heart rates are proposed. They significantly improved the accuracy in three light settings and a wide range of skin types categorized by the Fitzpatrick standard. Lastly, this work presents a new public dataset acquired from the forearm skin of 83 human subjects. The proposed method utilizes the Savitzky-Golay filter to treat components obtained by independent component analysis (ICA). We apply normalized autocorrelation to evaluate signals' period consistency and weigh ICA components accordingly. This method is a reliable way to accumulate weighted fast Fourier Transform spectra and compute the final frequency representing an estimated heart rate. In our experiments, the method significantly reduced the errors of prior methods in all of the three light settings, especially for ceiling fluorescent tubes where the errors were reduced by 83% on average.INDEX TERMS Independent component analysis, non-facial pulse measurement, iPPG, Fitzpatrick standard, FFT. I. INTRODUCTIONThe measurement of vital signs, such as heart rate, heart-rate variation, and respiratory rate, is essential to human wellness, especially for patient monitoring and diagnosis. At present,The associate editor coordinating the review of this manuscript and approving it for publication was Ganesh Naik .

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Section: E Proposed Ippg Methods On Non-facial Regionsmentioning

confidence: 99%

Robust Method for Non-Contact Vital Sign Measurement in Videos Acquired in Real-World Light Settings From Skin Less Affected by Blood Perfusion

Tangjui,

Taeprasartsit

2024

IEEE Access

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“…The window length neutralizes the high-frequency noise contribution for the second degree of freedom by smoothing its fluctuations through polynomial fitting 32,33 . The SG filter searches for the optimal n + 1 polynomial coefficients for a given n-degree polynomial to best suit the raw data and assesses the outcome in the window center 34,35 . The polynomial function was applied to the signal point by point.…”

Section: Spectral Pre-treatmentmentioning

confidence: 99%

Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis

Mulowayi,

Shen,

Nyimbo

et al. 2024

Sci Rep

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The study aimed to measure the carotenoid (Car) and pH contents of carrots using hyperspectral imaging. A total of 300 images were collected using a hyperspectral imaging system, covering 472 wavebands from 400 to 1000 nm. Regions of interest (ROIs) were defined to extract average spectra from the hyperspectral images (HIS). We developed two models: least squares support vector machine (LS-SVM) and partial least squares regression (PLSR) to establish a quantitative analysis between the pigment amounts and spectra. The spectra and pigment contents were predicted and correlated using these models. The selection of EWs for modeling was done using the Successive Projections Algorithm (SPA), regression coefficients (RC) from PLSR models, and LS-SVM. The results demonstrated that hyperspectral imaging could effectively evaluate the internal attributes of carrot cortex and xylem. Moreover, these models accurately predicted the Car and pH contents of the carrot parts. This study provides a valuable approach for variable selection and modeling in hyperspectral imaging studies of carrots.

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“…This paper uses the moving window least squares polynomial smoothing algorithm (Savitzky-Golay Smoothing) for data smoothing. The Savitzky-Golay Smoothing algorithm [10][11][12] was originally proposed by Savitzky and Golay in 1964 for smoothing and noise reduction of data streams and is now widely used in the image processing field. The algorithm is a least square based local fitting method that starts at the beginning of the stream and smooths the stream within a predetermined smoothing window, sliding backwards through the smoothing window until the end of the stream, the most important feature of the algorithm is that the shape, width and tendency of the stream remain unchanged while smoothing the data.…”

Section: Grey Gm(11) Prediction Model Improvementmentioning

confidence: 99%

Research on improved algorithms for network performance prediction based on grey prediction model

Chen,

Hong,

Jiang

et al. 2023

Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023)

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With the rapid development of computer networks, the scale of networks has become extremely large and complex, and a slight fluctuation in network performance parameters may have an impact on the entire network service, which makes accurate prediction of network performance particularly important. In this paper, an improved grey prediction model is applied to the prediction of network performance, and a Markov residual correction model is used to correct the prediction results to improve the prediction accuracy. The experimental results show that the error between the predicted and actual values after Markov residual correction is significantly reduced compared with the traditional grey prediction model, and the results are closer to the actual situation.

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On Employing a Savitzky-Golay Filtering Stage to Improve Performance of Spectrum Sensing in CR Applications Concerning VDSA Approach

Cited by 18 publications

References 10 publications

Robust Method for Non-Contact Vital Sign Measurement in Videos Acquired in Real-World Light Settings From Skin Less Affected by Blood Perfusion

Robust Method for Non-Contact Vital Sign Measurement in Videos Acquired in Real-World Light Settings From Skin Less Affected by Blood Perfusion

Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis

Research on improved algorithms for network performance prediction based on grey prediction model

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