Coding Prony’s method in MATLAB and applying it to biomedical signal filtering

Rodríguez, A. Fernández; Rodrigo, L. de Santiago; López-Guillén, Elena; Ascariz, José Manuel Rodríguez; Jiménez, Javier; Boquete, Luciano

doi:10.1186/s12859-018-2473-y

Cited by 40 publications

(27 citation statements)

References 62 publications

(53 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Rodríguez et al have conducted a review of Prony's method regarding the signal approximation using MATLAB code [29]. They have implemented the classical methods to test both performance and Prony approximation.…”

Section: Resultsmentioning

confidence: 99%

Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Abdulgani

Ahmad

2020

IEEE Access

View full text Add to dashboard Cite

Label-free methods neither cause cell damage nor contribute to any change in cell composition and intrinsic characteristics. Indeed, there is much interest in the scientific community to learn more from existing methods and to develop new label-free based methods for detection and classification of cells. Cell classification using optical measurements has been frequently utilized. When cells interact with light, due to differences in the composition of different types of cells, changes in the optical absorption and transmission response result. This work combined the advancement in optical measurements and Prony techniques to enhance the classification of cells based on their measured optical profiles. In this work, six types of cells, HeLa, 293T, lung-cancer and normal, and liver-cancer and normal, were suspended in their corresponding medium and their transmission characteristics were assessed. After media de-embedding, the transmission profiles were fitted with a sum of exponentially decaying signals using the Prony algorithm. After that, the optical response of each cell was modeled with a set of extracted parameters: amplitude, frequency, phase, and damping factor. The four parameters extracted via the Prony method are related to the coefficients and locations of the poles for each fitted model. A figure of merit (FOM) has been introduced, whose distribution in the complex z-plane plays a major role in the classification of cell type. The changes in the values of FOM are due to the changes in cell composition and intrinsic characteristics of different cells.

show abstract

Section: Resultsmentioning

confidence: 99%

Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Abdulgani

Ahmad

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…As previously described 20 , 23 , mfVEP signals were recorded monocularly with VERIS software 5.9 (Electro-Diagnostic Imaging, Inc., Redwood City, CA). The visual stimulus was a scaled dartboard with a diameter of 44.5 degrees, containing 60 sectors, each with 16 alternating checks.…”

Section: Methodsmentioning

confidence: 99%

Using advanced analysis of multifocal visual-evoked potentials to evaluate the risk of clinical progression in patients with radiologically isolated syndrome

Miguel-Jiménez

Roldán

Pérez-Rico

et al. 2021

Sci Rep

View full text Add to dashboard Cite

This study aimed to assess the role of multifocal visual-evoked potentials (mfVEPs) as a guiding factor for clinical conversion of radiologically isolated syndrome (RIS). We longitudinally followed a cohort of 15 patients diagnosed with RIS. All subjects underwent thorough ophthalmological, neurological and imaging examinations. The mfVEP signals were analysed to obtain features in the time domain (SNRmin: amplitude, Latmax: monocular latency) and in the continuous wavelet transform (CWT) domain (bmax: instant in which the CWT function maximum appears, Nmax: number of CWT function maximums). The best features were used as inputs to a RUSBoost boosting-based sampling algorithm to improve the mfVEP diagnostic performance. Five of the 15 patients developed an objective clinical symptom consistent with an inflammatory demyelinating central nervous system syndrome during follow-up (mean time: 13.40 months). The (SNRmin) variable decreased significantly in the group that converted (2.74 ± 0.92 vs. 4.07 ± 0.95, p = 0.01). Similarly, the (bmax) feature increased significantly in RIS patients who converted (169.44 ± 24.81 vs. 139.03 ± 11.95 (ms), p = 0.02). The area under the curve analysis produced SNRmin and bmax values of 0.92 and 0.88, respectively. These results provide a set of new mfVEP features that can be potentially useful for predicting prognosis in RIS patients.

show abstract

“…The Prony method, which is intended for use here, assumes that a sampled signal can be re-formulated as a linear combination of exponential functions [25][26][27][28]. This approach is not a spectral estimation technique, but it has a close relationship to squares linear prediction algorithms, which are usually used in auto-regressive (AR) or auto-regressive moving average (ARMA) parameter estimation methods.…”

Section: Post-processing Techniquesmentioning

confidence: 99%

Experimental Assessments on the Evaluation of Wire Rope Characteristics as Helical Symmetrical Multi-body Ensembles

2020

View full text Add to dashboard Cite

The existing literature provides various computational models related to the dynamic behavior of strand wire ropes. It starts from the simple longitudinally oscillating beam, to the complex nonlinear multi-body configuration based on helical structural symmetry. The challenge is the prior availability of characteristic parameters for material behavior, structural configuration, and functional capability. Experimental investigation is the main source for evaluation of these characteristics. However, tests have specifically been performed according to each case, minimizing the generalization aspect. This is the main frame of this study. Hereby, the authors propose an ensemble of spectral investigations, applied to a reduced set of experimental tests regarding wire rope dynamics. The research goal consists of wire rope characterization in terms of the flexible and adaptive groups of parameters, related to the conservative and dissipative behaviors. An experimental setup is considered here according to the rope exploitation conditions in order to enable an extension of the method application from the experimental mode to the operational mode. Experiments are conducted based on classical vibration measurement procedures. The analysis is performed using a spectral method ensemble, including discrete Fourier transform, time-frequency joint analysis, and the Prony method. The result show that the proposed assessments can provide suitable information related to a large group of wire rope models.

show abstract

Coding Prony’s method in MATLAB and applying it to biomedical signal filtering

Cited by 40 publications

References 62 publications

Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Using advanced analysis of multifocal visual-evoked potentials to evaluate the risk of clinical progression in patients with radiologically isolated syndrome

Experimental Assessments on the Evaluation of Wire Rope Characteristics as Helical Symmetrical Multi-body Ensembles

Contact Info

Product

Resources

About