Camilo La Rota Arango
My work Research Ph.D. thesis Publications Curriculum Vitae


Keywords: bioengineering, neuroengineering, signal processing, neurosciences, mathematical modeling

Research interests:

My research interests roughly lie in two general fields: biology (in particular neurosciences) and engineering (signal processing, mathematical modeling, circuits and systems), and in the intersection between them: either applications of engineering methods to study problems that arise in biology, neurosciences and medicine, or applications of biological principles to devise new engineering methods and systems.

My current research interests include, but are not limited to, the following areas and subjects:

  1. Biology and neuroscience :

  2. I have always been interested in understanding the principles behind complex biological activities, and more recently of those behind neural systems' functional activities. I find particularly exciting the study of the mechanisms underlying sensory information processing, perception, attention, conscioussness, movement planning and control, and other brain functions.

    My approach to these issues is both experimental and theoretical, and with a particular emphasis on the use of mathematical and computational methods.

  3. Signal processing, mathematical modeling, circuits and systems :

  4. This area correspond to my major educational background. The following are some of the subjects in which I have already worked or in which I would like to work in the future

  5. Mathematical and engineering methods applied to biology and neurosciences:

  6. With respect to applications, I am currently interested in the analysis of complex functional signals and images obtained with new multivariable and high resolution acquisition systems, as well as by the mathematical modeling of these signals in terms of the underlying biological processes. I have also interest in the mathematical modeling and simulation of complex biological systems, such as the neocortex, and on the theoretical study of their spatiotemporal activity patterns. Another exciting area of research that I expect to study is the development of new methods of interaction with neural tissues and with other complex biological systems.

    More precisely, the following are some of the subjects in which I have already worked or in which I expect to work in the near future:

    Even if my principal interests are in the beforementioned subjects, I am also motivated by other related problems such as the mathematical analysis of neural tissue development or the analysis of cardiovascular signals and the modeling of the.

  7. Applications of biological principles in engineering :

  8. Finally, I am interested on the development of information processing systems inspired on neurobiology, and of new neural based technological solutions for problems where sensing, perception and controled action are important issues (e.g. on neurorobotics).


Previous work :

Analisis of the electrical activity of the auditory cortex

During my Ph.D. thesis I have studied the electrical activity of the guinea pig's auditory cortex in response to stimuli. This problem was studied using both theoretical and experimental approaches, by means of multisite experimental data, mathematical modeling of the observed signals and data analyses based on stochastic processes models.

One of the objectives of this study was to understand auditory information processing at the cortex level with the aim of using this knowledge in auditory prosthesis design. One of the possible future practical developments of this work is the definition of a methodology to objectively characterize and compare the cortex activity produced by natural and by electrical stimulations, what may eventually be used to improve the quality of auditory prostheses.


EMG signal processing and feature extraction and prosthesis control

This work was developed during both my undergraduate project and my M.Sc. thesis. Here I have studied the problem of EMG signal processing and pattern recognition in order to produce adequate commands to control electromyographic hand prostheses. This study involved the development of an EMG signal's acquisition system, the use of standard data analysis methods (time and frequency domain methods, black-box model-based methods and multivariable statistical methods), and the development of a specific signal processing and pattern recognition methodology (based on neural networks, linear discriminant analysis and non-linear filtering)

The results were presented, and published in the proceedings, of the 10th ACIEM (Colombian association of electrical and mechanical engineers) conference in electronics and telecommunications.

Head MRI image analysis

Relationship between cardiovascular signals and motor activity

Multichannel evoked potentials acquisition


Work in progress :


Last modification: 27 Nov 2003