Examinando por Materia "Biomedical engineering"
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Ítem Analysis of chemical processes for the synthesis of magnetite for biomedical applications(IOP PUBLISHING LTD, 2011-01-01) Baena, J.; Marulanda, J.I.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaThis article demonstrates the evaluation of wet chemical routes to produce magnetic nanoparticles of iron oxide and surface chemistry characterization by infrared spectroscopy (IR). Its potential use in biomedicine as contrast agents or to deliver drugs in localized medical treatments, which reduce the toxicity associated with cytotoxic drugs, is also evaluated.Ítem Analysis of chemical processes for the synthesis of magnetite for biomedical applications(IOP PUBLISHING LTD, 2011-01-01) Baena, J.; Marulanda, J.I.; Baena, J.; Marulanda, J.I.; Universidad EAFIT. Departamento de Ciencias; Electromagnetismo Aplicado (Gema)This article demonstrates the evaluation of wet chemical routes to produce magnetic nanoparticles of iron oxide and surface chemistry characterization by infrared spectroscopy (IR). Its potential use in biomedicine as contrast agents or to deliver drugs in localized medical treatments, which reduce the toxicity associated with cytotoxic drugs, is also evaluated.Ítem An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y AplicacionesIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.Ítem An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.Ítem An approach to emotion recognition in single-channel EEG signals: A mother child interaction(IOP PUBLISHING LTD, 2016-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoIn this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains. Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadness.Ítem Cerebral Cortex Atlas of Emotional States Through EEG Processing(SPRINGER, 2019-10-14) Gómez A.; Quintero O.L.; Lopez-Celani N.; Villa L.F.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoThis paper addresses the cerebral cortex maps construction from EEG signals getting an information simplification method for an emotional state phenomenon description. Bi-dimensional density distribution of main signal features are identified and a comparison to a previous approach is presented. Feature extraction scheme is performed via windowed EEG signals Stationary Wavelet Transform with the Daubechies Family (1–10); nine temporal and spectral descriptors are computed from the decomposed signal. Recursive feature selection method based on training a Random forest classifier using a one-vs-all scheme with the full features space, then a ranking procedure via gini importance, eliminating the bottom features and restarting the entire process over the new subset. Stopping criteria is the maximum accuracy. The main contribution is the analysis of the resulting subset features as a proxy for cerebral cortex maps looking for the cognitive processes understanding from surface signals. Identifying the common location of different emotional states in the central and frontal lobes, allowing to be strong parietal and temporal lobes differentiators for different emotions. © 2020, Springer Nature Switzerland AG.Ítem Desarrollo de un modelo FEM del complejo craneofacial para simular tratamientos en CLASE III esqueletica(Facultad de Odontología, Universidad CES., 2010-01-01) María Eugenia González Botero; Isaza JF; Correa S; Roldán, S.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Bioingeniería GIB (CES – EAFIT)Introducción y Objetivo: Describir el método de reconstrucción de un cráneo completo para desarrollar un modelo de elementos finitos que permita posteriormente simular la acción de diferentes dispositivos tracción cervical mandibular, máscara facialÍtem Desarrollo de un modelo FEM del complejo craneofacial para simular tratamientos en CLASE III esqueletica(Facultad de Odontología, Universidad CES., 2010-01-01) María Eugenia González Botero; Isaza JF; Correa S; Roldán, S.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)Introducción y Objetivo: Describir el método de reconstrucción de un cráneo completo para desarrollar un modelo de elementos finitos que permita posteriormente simular la acción de diferentes dispositivos tracción cervical mandibular, máscara facialÍtem Design of an electrical power assist kit for manual wheelchair under the conditions of developing countries(2013-06-24) Mejía Gutiérrez, Ricardo; Zuluaga Holguín, Daniel; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ricardo Mejia (rmejiag@eafit.edu.co); Daniel Zuluaga (dzulua19@eafit.edu.co); Ingeniería de Diseño - GRIDElectric mobility has become an important issue worldwide; proof of this is that all the transportation areas are tending towards a green approach for their business by using renewable energies -- In parallel form, mobility for disabled people is a global concern right now, specifically how to improve the independency and raise the standard of living of people in this situation -- Electric mobility solutions have provided an important advance in the independency of patients -- However, as occurs with emerging technologies the price is quite high, especially for developing countries such as Colombia -- This work presents the design of an electric power kit for manual wheelchair, with the aim of making it adaptable for different wheelchair brands available in the Colombian marketÍtem Diseño y manufactura de un implante personalizado de cráneo(SPRINGER, 2013-01-01) Isaza, J.F.; Correa, S.; Franco, J.M.; Torres, C.; Bedoya, B.This paper describes the methodology used to design a custom-made cranial implant for a 26 year-old patient, who suffered a lesion in the left frontoparietal region of the skull caused by a fibrous dysplasia. The design of the implant was carried out from the 3D reconstruction of the skull of the patient, obtained by a CT- Scan, using Rapid Form 2006. Once the preliminary design was obtained, 3D models of the injured region of the skull and implant were fabricated in a Rapid Prototyping (RP) machine using the Fused Deposition Modeling Technology (FDM) with the purpose of making a functional and dimensional validation of the implant. Subsequently, the implant was fabricated in titanium alloy (Ti6Al4V). With the methodology, the prosthesis was successfully implanted. The surgical time decreased by 50%, compared with the same type of surgery in which standard commercial implants and titanium meshes are used; due, principally, to the need of implementing trial and error procedures, which intend to achieve a good fit of the implant increasing the risk of the patient. Finally, the aesthetic appearance of the patient was recovered, allowing the patient to safely perform daily activities. © 2013 Springer.Ítem Diseño y manufactura de un implante personalizado de cráneo(SPRINGER, 2013-01-01) Isaza, J.F.; Correa, S.; Franco, J.M.; Torres, C.; Bedoya, B.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Bioingeniería GIB (CES – EAFIT)This paper describes the methodology used to design a custom-made cranial implant for a 26 year-old patient, who suffered a lesion in the left frontoparietal region of the skull caused by a fibrous dysplasia. The design of the implant was carried out from the 3D reconstruction of the skull of the patient, obtained by a CT- Scan, using Rapid Form 2006. Once the preliminary design was obtained, 3D models of the injured region of the skull and implant were fabricated in a Rapid Prototyping (RP) machine using the Fused Deposition Modeling Technology (FDM) with the purpose of making a functional and dimensional validation of the implant. Subsequently, the implant was fabricated in titanium alloy (Ti6Al4V). With the methodology, the prosthesis was successfully implanted. The surgical time decreased by 50%, compared with the same type of surgery in which standard commercial implants and titanium meshes are used; due, principally, to the need of implementing trial and error procedures, which intend to achieve a good fit of the implant increasing the risk of the patient. Finally, the aesthetic appearance of the patient was recovered, allowing the patient to safely perform daily activities. © 2013 Springer.Ítem Double Fourier analysis for Emotion Identification in Voiced Speech(IOP PUBLISHING LTD, 2016-01-01) Sierra-Sosa, D.; Bastidas, M.; Ortiz, P.D.; Quintero, O.L.; Sierra-Sosa, D.; Bastidas, M.; Ortiz, P.D.; Quintero, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoWe propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.Ítem An Entropy-Based Graph Construction Method for Representing and Clustering Biological Data(SPRINGER, 2019-10-01) Ariza-Jiménez L.; Pinel N.; Villa L.F.; Quintero O.L.; Universidad EAFIT. Departamento de Ciencias; Ciencias Biológicas y Bioprocesos (CIBIOP)Unsupervised learning methods are commonly used to perform the non-trivial task of uncovering structure in biological data. However, conventional approaches rely on methods that make assumptions about data distribution and reduce the dimensionality of the input data. Here we propose the incorporation of entropy related measures into the process of constructing graph-based representations for biological datasets in order to uncover their inner structure. Experimental results demonstrated the potential of the proposed entropy-based graph data representation to cope with biological applications related to unsupervised learning problems, such as metagenomic binning and neuronal spike sorting, in which it is necessary to organize data into unknown and meaningful groups. © 2020, Springer Nature Switzerland AG.Ítem An Entropy-Based Graph Construction Method for Representing and Clustering Biological Data(SPRINGER, 2019-10-01) Ariza-Jiménez L.; Pinel N.; Villa L.F.; Quintero O.L.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoUnsupervised learning methods are commonly used to perform the non-trivial task of uncovering structure in biological data. However, conventional approaches rely on methods that make assumptions about data distribution and reduce the dimensionality of the input data. Here we propose the incorporation of entropy related measures into the process of constructing graph-based representations for biological datasets in order to uncover their inner structure. Experimental results demonstrated the potential of the proposed entropy-based graph data representation to cope with biological applications related to unsupervised learning problems, such as metagenomic binning and neuronal spike sorting, in which it is necessary to organize data into unknown and meaningful groups. © 2020, Springer Nature Switzerland AG.Ítem Handling Heterogeneity in Collaborative Networked Surgical Simulators(Universidad EAFIT, 2016) Díaz León, Christian Andrés; Trefftz Gómez, HelmuthStand-alone and networked surgical virtual reality based simulators have been proposed as means to train surgical skills with or without a supervisor nearby the student or trainee -- However, surgical skills teaching in medicine schools and hospitals is changing, requiring the development of new tools to focus on: (i) importance of mentors role, (ii) teamwork skills and (iii) remote training support -- For these reasons, a surgical simulator should not only allow the training involving a student and an instructor that are located remotely, but also the collaborative training of users adopting different medical roles during the training sesión -- Collaborative Networked Virtual Surgical Simulators (CNVSS) allow collaborative training of surgical procedures where remotely located users with different surgical roles can take part in the training session -- To provide successful training involving good collaborative performance, CNVSS should handle heterogeneity factors such as users’ machine capabilities and network conditions, among others -- Several systems for collaborative training of surgical procedures have been developed as research projects -- To the best of our knowledge none has focused on handling heterogeneity in CNVSS -- Handling heterogeneity in this type of collaborative sessions is important because not all remotely located users have homogeneous internet connections, nor the same interaction devices and displays, nor the same computational resources, among other factors -- Additionally, if heterogeneity is not handled properly, it will have an adverse impact on the performance of each user during the collaborative sesión -- In this document, the development of a context-aware architecture for collaborative networked virtual surgical simulators, in order to handle the heterogeneity involved in the collaboration session, is proposed -- To achieve this, the following main contributions are accomplished in this thesis: (i) Which and how infrastructure heterogeneity factors affect the collaboration of two users performing a virtual surgical procedure were determined and analyzed through a set of experiments involving users collaborating, (ii) a context-aware software architecture for a CNVSS was proposed and implemented -- The architecture handles heterogeneity factors affecting collaboration, applying various adaptation mechanisms and finally, (iii) A mechanism for handling heterogeneity factors involved in a CNVSS is described, implemented and validated in a set of testing scenariosÍtem Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.(IOP PUBLISHING LTD, 2016-01-01) Campo, D.; Quintero, O.L.; Bastidas, M.; Campo, D.; Quintero, O.L.; Bastidas, M.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoWe propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.Ítem Robotic research platform for image-guided surgery assistance(2013-01-01) Cortes, C.A.; Barandiaran, I.; Ruiz, O.E.; De Mauro, A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEIn the context of surgery, it is very common to face challenging scenarios during the preoperative plan implementation. The surgical technique's complexity, the human anatomical variability and the occurrence of unexpected situations generate issues for the intervention's goals achievement. To support the surgeon, robotic systems are being integrated to the operating room. However, current commercial solutions are specialized for a particular technique or medical application, being difficult to integrate with other systems. Thus, versatile and modular systems are needed to conduct several procedures and to help solving the problems that surgeons face. This article aims to describe the implementation of a robotic research platform prototype that allows novel applications in the field of image-guided surgery. In particular, this research is focused on the topics of medical image acquisition during surgery, patient registration and surgical/medical equipment operation. In this paper, we address the implementation of the general purpose teleoperation and path following modes of the platform, which constitute the base of future developments. Also, we discuss relevant aspects of the system, as well as future directions and application fields to investigate.Ítem A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies(IOP PUBLISHING LTD, 2016-01-01) Ortiz, P.D.; Villa, L.F.; Salazar, C.; Quintero, O.L.; Ortiz, P.D.; Villa, L.F.; Salazar, C.; Quintero, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoA simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals. The algorithm to define the dynamic threshold is a modification of a convex combination found in literature. This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise. The present work shows preliminary results over a database built with some political speech. The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared. Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works.Ítem Standardized Approaches for Assessing Metagenomic Contig Binning Performance from Barnes-Hut t-Stochastic Neighbor Embeddings(SPRINGER, 2020-01-01) Ceballos J.; Ariza-Jiménez L.; Pinel N.; Ceballos J.; Ariza-Jiménez L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Ciencias Biológicas y Bioprocesos (CIBIOP)The performance of unsupervised methods for metagenomic binning is often assessed using simulated microbial communities. The lack of well-characterized evaluation protocols and approaches to community construction cognizant of biological realities impedes the rigorous assessment and standardization of the binning process. This work attempted to standardize performance evaluation using benchmark communities constructed according to the genome similarity metric Average Amino Acid identity. This approach allowed us to extend and deepen our previous research on the unsupervised binning of metagenomic sequence fragments based on low-dimensional embeddings of pentamer frequency profiles. Experimental results evidenced our method’s potential for the binning of metagenomic contigs to become an alternative to state-of-the-art methods such as MetaCluster 3.0. © 2020, Springer Nature Switzerland AG.Ítem Standardized Approaches for Assessing Metagenomic Contig Binning Performance from Barnes-Hut t-Stochastic Neighbor Embeddings(SPRINGER, 2020-01-01) Ceballos J.; Ariza-Jiménez L.; Pinel N.; Ceballos J.; Ariza-Jiménez L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoThe performance of unsupervised methods for metagenomic binning is often assessed using simulated microbial communities. The lack of well-characterized evaluation protocols and approaches to community construction cognizant of biological realities impedes the rigorous assessment and standardization of the binning process. This work attempted to standardize performance evaluation using benchmark communities constructed according to the genome similarity metric Average Amino Acid identity. This approach allowed us to extend and deepen our previous research on the unsupervised binning of metagenomic sequence fragments based on low-dimensional embeddings of pentamer frequency profiles. Experimental results evidenced our method’s potential for the binning of metagenomic contigs to become an alternative to state-of-the-art methods such as MetaCluster 3.0. © 2020, Springer Nature Switzerland AG.