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Biomedical subjects

A B Barreto

Publications and source records attributed to A B Barreto.

3 recordsLinked to original sources

Delay measurement in dual blood volume pulse monitoring using adaptive signal processing techniques.

Two adaptive signal processing algorithms are applied to the estimation of the relative delay between Blood Volume Pulse (BVP) signals collected by independent sensors on the subject's index finger. Both the LMS Adaptive Predictor and the Adaptive Delay System are evaluated for the delay estimation in synthetic test signals and on actual pairs of BVP signals. The short-term variations in the relative delay of the BVP signals within a data record is studied and proposed as a key factor determining the better performance of the Adaptive Delay System. Changes in the estimated relative delay between the BVP signals of subjects before and after exercise are shown. It is proposed that these changes are associated with the modifications introduced in the cardiovascular system of the subject by exercise and can, therefore, be used to monitor the level of exercise achieved by a subject at different points in an exercise session.

Algorithms↗

STL: a spatio-temporal characterization of focal interictal events.

An innovative method for on-line processing of array ECoG data, the Spatio-Temporal Laplacian, intended for intraoperative epileptic focus localization is presented. This method simultaneously involves the spatial and temporal characteristics of the potential field manifestations peculiar to focal interictal events. A 3-Dimensional (x, y and t) sample space is used to explain and apply the Spatio-Temporal Laplacian (STL) transformation. In particular, a focal interictal event is detected through the coincident spatial and temporal sharpness that it introduces in this sample space. Preliminary results from two subjects are presented and compared with standard bioplar derivation signals, traditionally used in the focus localization task.

Adult↗

A practical EMG-based human-computer interface for users with motor disabilities.

In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities.

Biofeedback, Psychology↗