Biomedical subjects

Armando Barreto

Publications and source records attributed to Armando Barreto.

12 recordsLinked to original sources

PubMed2006

Enhanced real-time cursor control algorithm, based on the spectral analysis of electromyograms.

This paper presents a new version of an EMG-based, hands-free, cursor control system, and compares its performance to that of a previous version. Both systems use classification algorithms that rely on the periodogram estimation of the power spectral density (PSD) of electromyogram (EMG) signals from muscles in the face. The older system requires three electrodes for EMG input, and utilizes an algorithm that calculates partial power accumulations over the frequency ranges of 0Hz - 145Hz and 145Hz - 600Hz in the PSDs of the EMG signals. The new system requires four electrodes for EMG input, and utilizes an algorithm that calculates mean power frequency (MPF) values to assist in distinguishing the cranial muscle that contracted. An experiment was devised to gauge the point-and-click capabilities of both systems. The experimental results were evaluated using Fitts' Law analysis. The results show that the new algorithm provides improved point-and-click performance over the old algorithm.

Algorithms↗

PubMed2006

Biometric identification using 3D face scans.

Biometrics is an emerging area of bioengineering that pursues the characterization of a person by means of something that the person is or produces. Face recognition is a particularly attractive biometric challenge. Most of the face recognition research performed in the past used 2D intensity images. However, algorithms based on 2D images are not robust to changes of illumination in the environment or orientation of the subject. The ability to acquire 3D scans of human faces removes those ambiguities, since they capture the exact geometry of the subject, invariant to illumination and orientation changes. Unencumbered by those limitations, research in 3D face recognition is now beginning to address a different source of error in biometric recognition: facial geometry deformation caused by facial expressions, which can make 3D algorithms which treat 3D faces as rigid surfaces fail. In this paper, a 3D face recognition framework is proposed to tackle this problem. The framework is composed of three subsystems: expression recognition system, expressional face recognition system and neutral face recognition system. In particular, a system for the recognition of faces with one type of expression (smile) and neutral faces was implemented and tested on a database of 30 subjects. The results proved the feasibility of this framework.

Algorithms↗

PubMed2006

Stress detection in computer users through non-invasive monitoring of physiological signals.

he emerging discipline of Affective Computing pursues the development of computers that could interact with their users taking their affective states into account. For example, if a computer could detect when its user is experiencing stress, it could change the colors and sounds of its user interface to try to calm him/her down. Similarly, the pace of instruction in a computer-based training system could be adapted according to the stress level sensed in the pupil. The research described in this paper aims at the development of a stress detection approach based on automatic monitoring of physiological signals in the computer user. The paper describes the three main aspects of our work: experiment setup for physiological sensing, signal processing to detect the affective state and affective recognition using a learning system. Four signals: Galvanic Skin Response (GSR), Blood Volume Pulse (BVP), Pupil Diameter (PD) and Skin Temperature (ST) are monitored and analyzed to differentiate affective states in the user, in a non-invasive fashion. Results indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in emotional state of our experimental subjects when stress stimuli are applied to the interaction environment.

Adult↗

PubMed2005

Hands-free human computer interaction via an electromyogram-based classification algorithm.

A four-electrode system for hands-free computer cursor control, based on the digital processing of Electromyogram (EMG) signals is proposed. The electrodes are located over the right frontalis, the procerus, the left temporalis and the right temporalis muscles in the head. This system is meant to enable individuals paralyzed from the neck down (e.g., due to Spinal Cord Injury) to interact with computers using point-and-click graphic interfaces. The intention is to translate electromyograms derived from muscle contractions associated with specific facial movements into five cursor actions, namely: Left, Right, Up, Down and Left-click. This translation is accomplished by a digital signal processing classification algorithm that takes advantage of the divergent spectral nature of the EMG signals produced by the frontalis, temporalis, and procerus muscles, respectively. The effectiveness of the algorithm is evaluated by comparing its performance to that of a previously developed three-electrode EMG-based algorithm, using Matlab simulations. The results indicate that the algorithm classifies with great accuracy and provides a marked improvement over the previous three-electrode system.

Algorithms↗

PubMed2005

A bioinstrumentation system for the identification of EEG correlates of tinnitus.

Tinnitus is the spontaneous 'ringing' sensation within the auditory system reported by many individuals, which currently can only be diagnosed by behavioral response. Studies in this area have yet to identify definite mechanisms or sites associated with the generation of this sensation. The tinnitus sensation is typically reported to be prominent during silence. In addition, the complete withdrawal of auditory stimulus usually precedes the onset of the tinnitus sensation. This paper describes the conceptualization, integration and testing of an experimental instrument, developed to observe Auditory Evoked Potentials (AEPs) in order to identify possible EEG correlates of tinnitus. The instrumental setup permits the study of AEP responses during silence, as well as to observe the transitional nature of the AEP.

Algorithms↗

PubMed2005

Software-based compensation of visual refractive errors of computer users.

For human beings, vision is one of the most important senses in interacting with the surrounding environment, as well as with any tools that require visual communication. As such, the ability to interact effectively with computers through typical graphic user interfaces (GUIs) is greatly affected by any refractive errors present in an individual's visual system. If the refractive errors can be mathematically modeled, a system for overcoming these aberrations can be devised which can increase the effective human-computer interaction for these individuals. Several methods, such as Adaptive Optics, have been proposed that attempt to solve this problem using electro-mechanical devices. These methods are costly and impractical, preventing most visually impaired individuals from benefiting from their use. In contrast, an image-processing method, based on deconvolution techniques, has recently been proposed for the pre-compensation of images to be displayed in a computer. This method is much more practical, being completely implemented in software, and has achieved encouraging results. Previous results have yielded an average 50% increase in visual efficiency in the compensation of a known artificial aberration introduced into the field of vision of experimental subjects. This paper describes the difficulties encountered with the present software-only compensation and proposes several methods for overcoming these obstacles. The difficulties, as well as the proposed solutions, are described theoretically and followed by examples using a lens system showing the improvement over previous methods.

Algorithms↗

PubMed2004

Interictal spike detection using the Walsh transform.

The objective of this study was to evaluate the feasibility of using the Walsh transformation to detect interictal spikes in electroencephalogram (EEG) data. Walsh operators were designed to formulate characteristics drawn from experimental observation, as provided by medical experts. The merits of the algorithm are: 1) in decorrelating the data to form an orthogonal basis and 2) simplicity of implementation. EEG recordings were obtained at a sampling frequency of 500 Hz using standard 10-20 electrode placements. Independent sets of EEG data recorded on 18 patients with focal epilepsy were used to train and test the algorithm. Twenty to thirty minutes of recordings were obtained with each subject awake, supine, and at rest. Spikes were annotated independently by two EEG experts. On evaluation, the algorithm identified 110 out of 139 spikes identified by either expert (True Positives = 79%) and missed 29 spikes (False Negatives = 21%). Evaluation of the algorithm revealed a Precision (Positive Predictive Value) of 85% and a Sensitivity of 79%. The encouraging preliminary results support its further development for prolonged EEG recordings in ambulatory subjects. With these results, the false detection (FD) rate is estimated at 7.2 FD per hour of continuous EEG recording.

Action Potentials↗

PubMed2004

A new mathematical approach based on orthogonal operators for the detection of interictal spikes in epileptogenic data.

This study focuses on the design of orthogonal operators based on unique Electroencephalograph (EEG) signal decompositions in order to detect interictal spikes that characterize epileptic seizures in EEG data. The merits of the algorithm are: (a) in elaborating a unique analysis scheme that scrutinizes EEG data through orthogonal operators designed to extract features that best characterize spikes in epileptogenic EEG data; and (b) in establishing mathematical derivations that provide quantitative measures through the designed operators, and characterize and locate the event of an interictal spike. The uniqueness of this algorithm is in its good performance and simplicity of implementation. Clinical experiments involved 31 patients with focal epilepsy. EEG data collected from 10 of these patients were used initially in a training phase to ascertain the reliability of the observable and formulated features that were used in the spike detection process. Spikes were annotated independently by three EEG experts. On evaluation of the algorithm using the 21 remaining patients in the testing phase revealed a Precision (Positive Predictive Value) of 92% and a Sensitivity of 82%. Based on the 20 to 30-minute epochs of continuous EEG recording per subject, the false detection (FD) rate is estimated at 1.8 FD per hour of recorded EEG. These are good results that support further development of this algorithm for EEG diagnosis.

Action Potentials↗

PubMed2003

Design of a multi-sensor sonar system for indoor range measurement as a navigational aid for the blind.

This paper reports the methodology for the design of a sonar-based ranging and guidance system. The intended application of the system is to help a blind person avoid obstacles as he/she navigates his/her environment. Six sonar transceivers are arranged radially on a headgear worn by the user. The transceivers detect discrete range data at discrete-time sampling instances. A panoramic map of the environment is generated from the discrete-space sensory data. The paper emphasizes the challenges faced during the measurement of omnidirectional ranging information in indoor environments. Situations have been identified where erroneous range readings are generated due to channel cross talk caused by echo bouncing off multiple surfaces. Several sonar control and measurement schemes were developed and tested to avoid these situations. The results and performance of these different control schemes are compared in this paper. A microcontroller-based system commands the sonar ping sequences, acquires the echo return times and computes the ranges. The set of range data is transmitted to a PC, which utilizes the information to build a spatialized audio map of the surrounding obstacles. The hardware and software layout for the system are described in this paper.

Acoustics↗

PubMed2003

Digital image processing for pre-compensation of high-order aberrations of the human eye.

Human beings rely significantly on their visual capabilities to successfully interact with their environment. In today's technology-based world, one of the most important interaction channels is through computers. Some individuals with severe visual impairments may have difficulty in interacting with computers, even when using traditional means of visual correction (e.g., spectacles, contact lenses). This is, in part, because these correction mechanisms can only compensate for the most regular distortions or aberrations of the image in the eye. This paper proposes an image processing approach that will pre-compensate the images displayed on the computer screen, so as to counter the effect of the eye's aberrations on the image. The characterization of the eye required to perform this customized pre-compensation is the eye's Point Spread Function (PSF). The PSF can now be measured by a new generation of ophthalmic instruments generically called. Wavefront Analyzers.. The characterization provided by these instruments also includes the .higher-order aberration components. and could, therefore, lead to a more comprehensive vision correction than traditional mechanisms. The methods presented here will be explained in terms of their theoretical foundation and illustrated with results from the correction of aberrations introduced by lenses with known and constant PSFs.

Audiovisual Aids↗

PubMed2003

Digital signal processing methods for the evaluation of Blood Volume Pulse (BVP) waveform changes due to exercise.

Previous research by our group has revealed that the Blood Volume Pulse (BVP) waveform recorded using an infrared finger photoplethysmograph (PPG) undergoes changes as the subject performs physical exercise. In particular, a reduction in the depth of the Dicrotic Notch has been observed. There is an interest in characterizing those changes through a single parameter to measure the level of exercise the subject has reached, at any time during an exercise session. This paper reports on the comparison of three Digital Signal Processing approaches designed to reflect the BVP waveform changes through a single parameter, which could be obtained automatically from the digitized BVP signal. The first approach derives a single parameter from the distribution found in the average histogram of several time-aligned and averaged BVP beats. Our second approach analyzes the ratio observed between the first harmonic and higher harmonics in the BVP signal. The third approach evaluates the Dicrotic Notch depth directly from the BVP waveform, tracking sample values about the local minimum defined by the Dicrotic Notch. Our study, involving observations from 10 subjects, ranks these three approaches according to their ability to reflect the changes in BVP due to exercise.

Adult↗

PubMedDate not supplied

Detection of interictal spikes and artifactual data through orthogonal transformations.

This study introduces an integrated algorithm based on the Walsh transform to detect interictal spikes and artifactual data in epileptic patients using recorded EEG data. The algorithm proposes a unique mathematical use of Walsh-transformed EEG signals to identify those criteria that best define the morphologic characteristics of interictal spikes. EEG recordings were accomplished using the 10-20 system interfaced with the Electrical Source Imaging System with 256 channels (ESI-256) for enhanced preprocessing and on-line monitoring and visualization. The merits of the algorithm are: (1) its computational simplicity; (2) its integrated design that identifies and localizes interictal spikes while automatically removing or discarding the presence of different artifacts such as electromyography, electrocardiography, and eye blinks; and (3) its potential implication to other types of EEG analysis, given the mathematical basis of this algorithm, which can be patterned or generalized to other brain dysfunctions. The mathematics that were applied here assumed a dual role, that of transforming EEG signals into mutually independent bases and in ascertaining quantitative measures for those morphologic characteristics deemed important in the identification process of interictal spikes. Clinical experiments involved 31 patients with focal epilepsy. EEG data collected from 10 of these patients were used initially in a training phase to ascertain the reliability of the observable and formulated features that were used in the spike detection process. Three EEG experts annotated spikes independently. On evaluation of the algorithm using the 21 remaining patients in the testing phase revealed a precision (positive predictive value) of 92% and a sensitivity of 82%. Based on the 20- to 30-minute epochs of continuous EEG recording per subject, the false detection rate is estimated at 1.8 per hour of continuous EEG. These are positive results that support further development of this algorithm for prolonged EEG recordings on ambulatory subjects and to serve as a support mechanism to the decisions made by EEG experts.

Action Potentials↗