Papers by Mario Martinez-Zarzuela
Scientific Data, 10, 2023
Human activity recognition and clinical biomechanics are challenging problems in physical telereh... more Human activity recognition and clinical biomechanics are challenging problems in physical telerehabilitation medicine. However, most publicly available datasets on human body movements cannot be used to study both problems in an out-of-the-lab movement acquisition setting. The objective of the VIDIMU dataset is to pave the way towards affordable patient gross motor tracking solutions for daily life activities recognition and kinematic analysis. The dataset includes 13 activities registered using a commodity camera and five inertial sensors. The video recordings were acquired in 54 subjects, of which 16 also had simultaneous recordings of inertial sensors. The novelty of dataset lies in: (i) the clinical relevance of the chosen movements, (ii) the combined utilization of affordable video and custom sensors, and (iii) the implementation of state-of-the-art tools for multimodal data processing of 3D body pose tracking and motion reconstruction in a musculoskeletal model from inertial data. The validation confirms that a minimally disturbing acquisition protocol, performed according to real-life conditions can provide a comprehensive picture of human joint angles during daily life activities.
Procedia Computer Science, 2015
Ix Jornades De Xarxes D Investigacio En Docencia Universitaria Recurso Electronico Disseny De Bones Practiques Docents En El Context Actual Jornadas De Redes De Investigacion En Docencia Universitaria Diseno De Buenas Practicas Docentes En El Contexto Actual 2011 Isbn 978 84 694 9813 2, 2011
Revistaesalud Com, 2013
Cocina virtual para ayudar en la rehabilitación de personas con lesiones cerebrales mediante entr... more Cocina virtual para ayudar en la rehabilitación de personas con lesiones cerebrales mediante entrenamiento en una actividad cotidiana
Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health, 2015
Lecture Notes in Computer Science, 2009
Programming of Graphics Processing Units (GPUs) has evolved in a way they can be used to address ... more Programming of Graphics Processing Units (GPUs) has evolved in a way they can be used to address and speed-up computation of algorithms exemplified by data-parallel models. In this paper parallelization of a Fuzzy ART algorithm is described and a detailed explanation of its implementation under CUDA is given. Experimental results show the algorithm runs up to 52 times faster on
Lecture Notes in Computer Science, 2009
This paper presents a supervised neural architecture, called SOON, for texture classification. Mu... more This paper presents a supervised neural architecture, called SOON, for texture classification. Multi-scale Gabor filtering is used to extract the textural features which shape the input to a neural classifier with orientation invariance properties in order to accomplish the ...
Lecture Notes in Computer Science, 2006
... were taken by us with the Logitech QuickCam Zoom and the Genius VideoCAM Web cams with ... th... more ... were taken by us with the Logitech QuickCam Zoom and the Genius VideoCAM Web cams with ... the modules of the preprocessing stage from an image captured by a webcam are shown ... 5. Heisele, B., Ho, P., Wu, J., Poggio, T.: Face recognition: component-based versus global ...
When tracking a human body, action recognition tasks can be performed to determine what kind of m... more When tracking a human body, action recognition tasks can be performed to determine what kind of movement the person is performing. Although a lot of implementations have emerged, state-of-the-art technology such as depth cameras and intelligent systems can be used to b uild a robust system. This paper describes the process of building a system of this type, from the construction of the dataset to o btain the tracked motion information in the front-end, to the pattern classification backend. The tracking process is performed using the Microsoft(R) Kinect hardware, which allows a reliable way t o store the trajectories of subjects. Then, signal processing techniques are applied on these trajectories to build action patterns, which feed a Fuzzy-based Neural Network adapted to this purpose. Two different tests were conducted using the proposed system. Recognition among 5 whole body actions executed by 9 humans achieves 91.1% of success rate, while recognition among 10 actions is done with an accuracy of 81.1%.
Encyclopedia of Artificial Intelligence, 2009
Concepts, Methodologies, Tools and Applications, 2011
Encyclopedia of Information Science and Technology, Third Edition, 2015
Applied Soft Computing, 2014
ABSTRACT In this paper, a new neural model for bio-inspired processing of color images, called dP... more ABSTRACT In this paper, a new neural model for bio-inspired processing of color images, called dPREEN (double recurrent Perceptual boundaRy dEtection Neural) model, is presented. The dPREEN model includes a double feedback among V1, V2 and V4 cortical areas, simple and double color opponent processes, orientation filtering using Gabor kernels, surround suppression in complex cells, top-down and bottom-up information fusion and chromatic diffusion, to generate contours of perceptual significance in color natural scenes. The outputs of the model are a boundary map of the scene and surface perception images. This paper incorporates a comparative analysis of the proposed model against two other contour extraction methods in the Berkeley Segmentation Dataset and Benchmark. The analysis shows favorable results to the dPREEN model. Additionally, this paper describes two parallel implementations of the model for its execution on Graphics Processing Units.
Lecture Notes in Computer Science, 2011
In this paper we introduce, to the best of our knowledge, the first adaptation of the Fuzzy ARTMA... more In this paper we introduce, to the best of our knowledge, the first adaptation of the Fuzzy ARTMAP neural network for its execution on a GPU, together with a self-designed neural network based on ART models called SOON. The full VisTex database, containing 167 texture images, is proved to be classified in a very short time using these GPU-based neural networks. The Fuzzy ARTMAP neural network implemented on the GPU performs up to ×100 times faster than the equivalent CPU version, while the SOON neural network is speeded-up by ×70 times. Also, using the same texture patterns the Fuzzy ARTMAP neural network obtains a success rate of 48% and SOON of 82% for texture classification.
Lecture Notes in Computer Science, 2011
In this paper we introduce a neural architecture for multiple scale color image segmentation on a... more In this paper we introduce a neural architecture for multiple scale color image segmentation on a Graphics Processing Unit (GPU): the BioSPCIS (Bio-Inspired Stream Processing Color Image Segmentation) architecture. BioSPCIS has been designed according to the physiological organization of the cells on the mammalian visual system and psychophysical studies about the interaction of these cells for image segmentation. Quality of
PLoS ONE, 2014
Information theory allows us to investigate information processing in neural systems in terms of ... more Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and artificial systems. Citation: Wollstadt P, Martínez-Zarzuela M, Vicente R, Díaz-Pernas FJ, Wibral M (2014) Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series. PLoS ONE 9(7): e102833.
2005 IEEE Conference on Emerging Technologies and Factory Automation, 2005
This paper introduces an Intelligent Transport System we called SigFlot, which is specially desig... more This paper introduces an Intelligent Transport System we called SigFlot, which is specially designed for fleet management, using dynamic information. Its main objective is to optimally manage the resources of a transport enterprise in order to achieve a safer and more efficient transport. The system consists of one set of modules which perform different jobs: communications (GSM/SMS), location (GPS), hiring / info through the Web, geographic information (GIS), route optimizing (Dijkstra algorithm and Taboo search). This application is fully developed in Java so it eases its portability to other platforms and OS.
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Papers by Mario Martinez-Zarzuela