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Pereira-Montiel E, Pérez-Giraldo E, Mazo J, Orrego-Metaute D, Delgado-Trejos E, Cuesta-Frau D, Murillo-Escobar J. Automatic sign language recognition based on accelerometry and surface electromyography signals: A study for Colombian sign language. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Goez MM, Torres-Madronero MC, Rothlisberger S, Delgado-Trejos E. Joint pre-processing framework for two-dimensional gel electrophoresis images based on nonlinear filtering, background correction and normalization techniques. BMC Bioinformatics 2020; 21:376. [PMID: 32867673 PMCID: PMC7457503 DOI: 10.1186/s12859-020-03713-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 08/18/2020] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND Two-dimensional gel electrophoresis (2-DGE) is a commonly used tool for proteomic analysis. This gel-based technique separates proteins in a sample according to their isoelectric point and molecular weight. 2-DGE images often present anomalies due to the acquisition process, such as: diffuse and overlapping spots, and background noise. This study proposes a joint pre-processing framework that combines the capabilities of nonlinear filtering, background correction and image normalization techniques for pre-processing 2-DGE images. Among the most important, joint nonlinear diffusion filtering, adaptive piecewise histogram equalization and multilevel thresholding were evaluated using both synthetic data and real 2-DGE images. RESULTS An improvement of up to 46% in spot detection efficiency was achieved for synthetic data using the proposed framework compared to implementing a single technique of either normalization, background correction or filtering. Additionally, the proposed framework increased the detection of low abundance spots by 20% for synthetic data compared to a normalization technique, and increased the background estimation by 67% compared to a background correction technique. In terms of real data, the joint pre-processing framework reduced the false positives up to 93%. CONCLUSIONS The proposed joint pre-processing framework outperforms results achieved with a single approach. The best structure was obtained with the ordered combination of adaptive piecewise histogram equalization for image normalization, geometric nonlinear diffusion (GNDF) for filtering, and multilevel thresholding for background correction.
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Affiliation(s)
- Manuel Mauricio Goez
- Smart Machine and Pattern Recognition Laboratory - MIRP, Faculty of Engineering, Instituto Tecnologico Metropolitano ITM, Medellin, 050012 Colombia
| | - Maria C. Torres-Madronero
- Smart Machine and Pattern Recognition Laboratory - MIRP, Faculty of Engineering, Instituto Tecnologico Metropolitano ITM, Medellin, 050012 Colombia
| | - Sarah Rothlisberger
- Biomedical Innovation and Research Group, Faculty of Applied and Exact Sciences, Instituto Tecnologico Metropolitano ITM, Medellin, 050034 Colombia
| | - Edilson Delgado-Trejos
- AMYSOD Lab (Parque i), CM&P Research Group, Quality and Production Department, Instituto Tecnologico Metropolitano ITM, Medellin, 050034 Colombia
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Murillo-Escobar J, Jaramillo-Munera YE, Orrego-Metaute DA, Delgado-Trejos E, Cuesta-Frau D. Muscle fatigue analysis during dynamic contractions based on biomechanical features and Permutation Entropy. Math Biosci Eng 2020; 17:2592-2615. [PMID: 32233556 DOI: 10.3934/mbe.2020142] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Muscle fatigue is an important field of study in sports medicine and occupational health. Several studies in the literature have proposed methods for predicting muscle fatigue in isometric con-tractions using three states of muscular fatigue: Non-Fatigue, Transition-to-Fatigue, and Fatigue. For this, several features in time, spectral and time-frequency domains have been used, with good performance results; however, when they are applied to dynamic contractions the performance decreases. In this paper, we propose an approach for analyzing muscle fatigue during dynamic contractions based on time and spectral domain features, Permutation Entropy (PE) and biomechanical features. We established a protocol for fatiguing the deltoid muscle and acquiring surface electromiography (sEMG) and biomechanical signals. Subsequently, we segmented the sEMG and biomechanical signals of every contraction. In order to label the contraction, we computed some features from biomechanical signals and evaluated their correlation with fatigue progression, and the most correlated variables were used to label the contraction using hierarchical clustering with Ward's linkage. Finally, we analyzed the discriminant capacity of sEMG features using ANOVA and ROC analysis. Our results show that the biomechanical features obtained from angle and angular velocity are related to fatigue progression, the analysis of sEMG signals shows that PE could distinguish Non-Fatigue, Transition-to-Fatigue and Fatigue more effectively than classical sEMG features of muscle fatigue such as Median Frequency.
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Affiliation(s)
- J Murillo-Escobar
- Department of Exact and Applied Sciences, GI2B Research Group, Instituto Tecnologico Metropolitano ITM, CL 73 No. 76 A 354, Medellin, Colombia
| | - Y E Jaramillo-Munera
- Department of Exact and Applied Sciences, GI2B Research Group, Instituto Tecnologico Metropolitano ITM, CL 73 No. 76 A 354, Medellin, Colombia
| | - D A Orrego-Metaute
- Department of Exact and Applied Sciences, GI2B Research Group, Instituto Tecnologico Metropolitano ITM, CL 73 No. 76 A 354, Medellin, Colombia
| | - E Delgado-Trejos
- AMYSOD Lab -Parque i, CM&P Research Group, Instituto Tecnologico Metropolitano ITM, CL 73 No. 76 A 354, Medellin, Colombia
| | - D Cuesta-Frau
- Technological Institute of Informatics, Universitat Politecnica de Valencia, Alcoi Campus, 03801 Alcoi, Spain
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Goez MM, Torres-Madroñero MC, Röthlisberger S, Delgado-Trejos E. Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review. Genomics Proteomics Bioinformatics 2018; 16:63-72. [PMID: 29474888 PMCID: PMC6000252 DOI: 10.1016/j.gpb.2017.10.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 09/20/2017] [Accepted: 10/19/2017] [Indexed: 12/19/2022]
Abstract
Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8-20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10-20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20-14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.
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Affiliation(s)
- Manuel Mauricio Goez
- Automatics, Electronics and Computer Science Research Group, Faculty of Engineering, Instituto Tecnologico Metropolitano, Medellin 050012, Colombia
| | - Maria Constanza Torres-Madroñero
- Automatics, Electronics and Computer Science Research Group, Faculty of Engineering, Instituto Tecnologico Metropolitano, Medellin 050012, Colombia.
| | - Sarah Röthlisberger
- Biomedical Innovation and Research Group, Faculty of Applied and Exact Sciences, Instituto Tecnologico Metropolitano, Medellin 050012, Colombia
| | - Edilson Delgado-Trejos
- Quality, Metrology and Production Research Group, Faculty of Economic and Management Sciences, Instituto Tecnologico Metropolitano, Medellin 050012, Colombia
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Pineda Guerra Y, Betancur Echeverri J, Pedroza-Díaz J, Delgado-Trejos E, Röthlisberger S. Análisis proteómico del veneno de la abeja africanizada: comparación de métodos de extracción. Acta biol Colomb 2016. [DOI: 10.15446/abc.v21n3.54046] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
La abeja africanizada es la más común en la apicultura colombiana y a su veneno (apitoxina) se le han atribuido propiedades terapéuticas para diferentes enfermedades, sin mayor soporte científico. Al revisar en la literatura los reportes publicados sobre el análisis proteómico de la apitoxina, se encontraron cuatro métodos distintos para la extracción de proteínas de la apitoxina. El primer método consiste en resuspender la apitoxina en Urea 7 M, precipitar con acetona y finalmente resuspender en Urea 7 M y CHAPS 4 %. Para el segundo método se resuspende la apitoxina en buffer de lisis, se precipita con ácido tricloroacético, y luego se resuspende en Urea 7 M y CHAPS 4 %. El tercer método es igual al anterior, excepto que la precipitación se realiza con acetona en vez de ácido tricloroacético. Finalmente, el cuarto método consiste en resuspender la apitoxina en agua destilada, precipitar con acetona y resuspender en Urea 7 M y CHAPS 4 %. Este trabajo se enfocó en comparar el desempeño de estos cuatro métodos de extracción y determinar el método con el mejor resultado en cuanto a la concentración e integridad obtenida de las proteínas. De los distintos métodos evaluados, se encontró que los mejores resultados en cuanto a concentración de proteínas se obtuvieron con la resuspensión de apitoxina en buffer de lisis y precipitación con acetona (método 3) y con el método de resuspensión de apitoxina en agua destilada y precipitación con acetona (método 4). De estos, el mejor método de extracción en cuanto a integridad de las proteínas y perfil proteómico fue el de resuspensión de apitoxina en buffer de lisis seguido de precipitación con acetona (método 3).
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Becerra MA, Orrego DA, Delgado-Trejos E. Adaptive neuro-fuzzy inference system for acoustic analysis of 4-channel phonocardiograms using empirical mode decomposition. Annu Int Conf IEEE Eng Med Biol Soc 2013; 2013:969-72. [PMID: 24109851 DOI: 10.1109/embc.2013.6609664] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The heart's mechanical activity can be appraised by auscultation recordings, taken from the 4-Standard Auscultation Areas (4-SAA), one for each cardiac valve, as there are invisible murmurs when a single area is examined. This paper presents an effective approach for cardiac murmur detection based on adaptive neuro-fuzzy inference systems (ANFIS) over acoustic representations derived from Empirical Mode Decomposition (EMD) and Hilbert-Huang Transform (HHT) of 4-channel phonocardiograms (4-PCG). The 4-PCG database belongs to the National University of Colombia. Mel-Frequency Cepstral Coefficients (MFCC) and statistical moments of HHT were estimated on the combination of different intrinsic mode functions (IMFs). A fuzzy-rough feature selection (FRFS) was applied in order to reduce complexity. An ANFIS network was implemented on the feature space, randomly initialized, adjusted using heuristic rules and trained using a hybrid learning algorithm made up by least squares and gradient descent. Global classification for 4-SAA was around 98.9% with satisfactory sensitivity and specificity, using a 50-fold cross-validation procedure (70/30 split). The representation capability of the EMD technique applied to 4-PCG and the neuro-fuzzy inference of acoustic features offered a high performance to detect cardiac murmurs.
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Orrego DA, Becerra MA, Delgado-Trejos E. Dimensionality reduction based on fuzzy rough sets oriented to ischemia detection. Annu Int Conf IEEE Eng Med Biol Soc 2013; 2012:5282-5. [PMID: 23367121 DOI: 10.1109/embc.2012.6347186] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
This paper presents a dimensionality reduction study based on fuzzy rough sets with the aim of increasing the discriminant capability of the representation of normal ECG beats and those that contain ischemic events. A novel procedure is proposed to obtain the fuzzy equivalence classes based on entropy and neighborhood techniques and a modification of the Quick Reduct Algorithm is used to select the relevant features from a large feature space by a dependency function. The tests were carried out on a feature space made up by 840 wavelet features extracted from 900 ECG normal beats and 900 ECG beats with evidence of ischemia. Results of around 99% classification accuracy are obtained. This methodology provides a reduced feature space with low complexity and high representation capability. Additionally, the discriminant strength of entropy in terms of representing ischemic disorders from time-frequency information in ECG signals is highlighted.
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Affiliation(s)
- Diana A Orrego
- SINERGIA Research Group of the Instituto Tecnologico Metropolitano ITM, Calle 73 No. 76A-354, Medellin, Colombia.
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Martinez-Tabares FJ, Delgado-Trejos E, Castellanos-Dominguez G. Wearable and superhydrophobic hardware for ambulatory biopotential acquisition. Annu Int Conf IEEE Eng Med Biol Soc 2013; 2013:1847-1850. [PMID: 24110070 DOI: 10.1109/embc.2013.6609883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Wearable monitoring devices are a promising trend for ambulatory and real time biosignal processing, because they improve access and coverage by means of comfortable sensors, with real-time communication via mobile networks. In this paper, we present a garment for ambulatory electrocardiogram monitoring, a smart t-shirt with a textile electrode that conducts electricity and has a coating designed to preserve the user's hygiene, allowing long-term mobile measurements. Silicon dioxide nanoparticles were applied on the surface of the textile electrodes to preserve conductivity and impart superhydrophobic properties. A model to explain these results is proposed. The best result of this study is obtained when the contact angles between the fluid and the fabric exceeded 150°, while the electrical resistivity remained below 5 Ω·cm, allowing an acquisition of high quality electrocardiograms in moving patients. Thus, this tool represents an interesting alternative for medium and long-term measurements, preserving the textile feeling of clothing and working under motion conditions.
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Rodríguez-Sotelo JL, Delgado-Trejos E, Peluffo-Ordóñez D, Cuesta-Frau D, Castellanos-Domínguez G. Weighted-PCA for unsupervised classification of cardiac arrhythmias. Annu Int Conf IEEE Eng Med Biol Soc 2010; 2010:1906-9. [PMID: 21096570 DOI: 10.1109/iembs.2010.5627321] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
A method that improves the feature selection stage for non-supervised analysis of Holter ECG signals is presented. The method corresponds to WPCA approach developed mainly in two stages. First, the weighting of the feature set through a weight vector based on M-inner product as distance measure and a quadratic optimization function. The second one is the linear projection of weighted data using principal components. In the clustering stage, some procedures are considered: estimation of the number of groups, initialization of centroids and grouping by means a soft clustering algorithm. In order to decrease the procedure computational cost, segment analysis, grouping contiguous segments and establishing union and exclusion criteria per each cluster, is carried out. This work is focused to classify cardiac arrhythmias into 5 groups, according to the standard of the AAMI (ANSI/AAMI EC57:1998/ 2003). To validate the method, some recordings from MIT/BIH arrhythmia database are used. By employing the labels of each recording, the performance is assessed with supervised measures (Se = 90.1%, Sp = 98.9% y Cp = 97.4%), enhancing other works in the literature that do not take into account all heartbeat types.
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Affiliation(s)
- J L Rodríguez-Sotelo
- Faculty of Electrical and Electronic Engineering, Universidad Nacional de Colombia sede Manizales, Colombia.
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Sarria-Paja M, Castellanos-Dominguez G, Delgado-Trejos E. A new approach to discriminative HMM training for pathological voice classification. Annu Int Conf IEEE Eng Med Biol Soc 2010; 2010:4674-4677. [PMID: 21096005 DOI: 10.1109/iembs.2010.5626408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
This paper presents a new approach that improves discriminative training criterion for Hidden Markov Models, and is oriented to pathological voice identification. This technique is aimed at maximizing the Area under the Curve of a receiver operating characteristic curve by adjusting the model parameters using as objective function the Mahalanobis distance and the distance between means of the underlying probability density functions associated with each class. The results show that the proposed technique significantly outperforms the accuracy in a classification system compared with other training criteria. Results are provided using the MEEIVL voice disorders database.
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Affiliation(s)
- M Sarria-Paja
- Research Center in Instituto Tecnológico Metropolitano, Medellín Colombia.
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Guarín-Lopez D, Orozco-Gutierrez A, Delgado-Trejos E, Guijarro-Estelles E. On detecting determinism and nonlinearity in microelectrode recording signals: approach based on non-stationary surrogate data methods. Annu Int Conf IEEE Eng Med Biol Soc 2010; 2010:4032-4035. [PMID: 21097286 DOI: 10.1109/iembs.2010.5628096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Two new surrogate methods, the Small Shuffle Surrogate (SSS) and the Truncated Fourier Transform Surrogate (TFTS), have been proposed to study whether there are some kind of dynamics in irregular fluctuations and if so whether these dynamics are linear or not, even if this fluctuations are modulated by long term trends. This situation is theoretically incompatible with the assumption underlying previously proposed surrogate methods. We apply the SSS and TFTS methods to microelectrode recording (MER) signals from different brain areas, in order to acquire a deeper understanding of them. Through our methodology we conclude that the irregular fluctuations in MER signals possess some determinism.
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Affiliation(s)
- D Guarín-Lopez
- Department of Electrical Engineering, Universidad Tecnológica de Pereira, Colombia.
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Delgado-Trejos E, Perera-Lluna A, Vallverdú-Ferrer M, Caminal-Magrans P, Castellanos-Domínguez G. Dimensionality reduction oriented toward the feature visualization for ischemia detection. IEEE Trans Inf Technol Biomed 2009; 13:590-8. [PMID: 19304491 DOI: 10.1109/titb.2009.2016654] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
An effective data representation methodology on high-dimension feature spaces is presented, which allows a better interpretation of subjacent physiological phenomena (namely, cardiac behavior related to cardiovascular diseases), and is based on search criteria over a feature set resulting in an increase in the detection capability of ischemic pathologies, but also connecting these features with the physiologic representation of the ECG. The proposed dimension reduction scheme consists of three levels: projection, interpretation, and visualization. First, a hybrid algorithm is described that projects the multidimensional data to a lower dimension space, gathering the features that contribute similarly in the meaning of the covariance reconstruction in order to find information of clinical relevance over the initial training space. Next, an algorithm of variable selection is provided that further reduces the dimension, taking into account only the variables that offer greater class separability, and finally, the selected feature set is projected to a 2-D space in order to verify the performance of the suggested dimension reduction algorithm in terms of the discrimination capability for ischemia detection. The ECG recordings used in this study are from the European ST-T database and from the Universidad Nacional de Colombia database. In both cases, over 99% feature reduction was obtained, and classification precision was over 99% using a five-nearest-neighbor classifier (5-NN).
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Affiliation(s)
- Edilson Delgado-Trejos
- Machine Intelligence and Pattern Recognition Group, Research Center, Instituto Tecnológico Metropolitano, Medellín 57, Colombia.
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