Bioelectrical signal processing in cardiac and neurological applications and electromyography: physiology, engineering, and noninvasive applications

The present article reviews two recent books dealing with rather closely related subjects; in fact, they tend to complement and supplement reciprocally. Obviously, the electromyogram is a bioelectrical signal that often is mathematically manipulated in different ways to better extract its information. Moreover, its correlation with other bioelectric variables may become necessary

50 years a biomedical engineer remembering a long and fascinating journey

Looking back at one point of life appears as a nice exercise to round out and summarize. However, the objective should not be simply to tell a story; it must transmit a message to the young. To start with, two concepts are useful: Respect for others begins when you learn to laugh at yourself and, taken from an old saying, I did not want to be poor ... but money wouldn't make me rich. After elementary and high schools, during times of turmoil, I describe my engineering school years at the University of Buenos Aires and a working experience in an international telecommunications company. Significant events taught me a concept, rooted in another motto: Isn't this house nice? It is my house, and I love it very much. In 1960, I began my activities in the USA. A couple of bad decisions resulted in significant events for me teaching me an important truth: "Beware of golden promises; time is the most precious asset". Finally, in 1972, settled down in Tucumán until retirement in 2001, a long period of productive activity came about, not without difficulties and also stained by a dark political interval. Crises seem to characterize our generations in Argentina. Non-the-less, there were some real accomplishments: an undergraduate program in BME and a National BME Society (SABI) plus an archive of specialized published material. After spending time following retirement in Peru and Italy, my current activity came as unexpected dessert at the University of Buenos Aires, with a small research group, so offering the opportunity of transmitting what I still have available

Neuroendocrinology and its Quantitative Development: A Bioengineering View

Biomedical engineering is clearly present in modern neuroendocrinology, and indeed has come to embrace it in many respects. First, we briefly review the origins of endocrinology until neuroendocrinology, after a long saga, was established in the 1950's decade with quantified results made possible by the radioimmunoassay technique (RIA), a development contributed by the physical sciences. However, instrumentation was only one face of the quantification process, for mathematical models aiding in the study of negative feedback loops, first rather shyly and now at a growing rate, became means building the edifice of mathematical neuroendocrinology while computer assisted techniques help unravel the associated genetic aspects or the nature itself of endocrine bursts by numerical deconvolution analysis. To end the note, attention is called to the pleiotropic characteristics of neuroendocrinology, which keeps branching off almost endlessly as bioengineering does too

Honoring Leslie A. Geddes - Farewell ...

Honor thy father and thy mother, say the Holy Scriptures[1], for they at least gave thee this biological life, but honor thy teachers, too, for they gave thee knowledge and example

Probability of ventricular fibrillation: allometric model based on the ST deviation

<p>Abstract</p> <p>Background</p> <p>Allometry, in general biology, measures the relative growth of a part in relation to the whole living organism. Using reported clinical data, we apply this concept for evaluating the probability of ventricular fibrillation based on the electrocardiographic ST-segment deviation values.</p> <p>Methods</p> <p>Data collected by previous reports were used to fit an allometric model in order to estimate ventricular fibrillation probability. Patients presenting either with death, myocardial infarction or unstable angina were included to calculate such probability as, <it>VF</it>_{<it>p </it>}<it>= δ + β (ST)</it>, for three different ST deviations. The coefficients <it>δ </it>and <it>β </it>were obtained as the best fit to the clinical data extended over observational periods of 1, 6, 12 and 48 months from occurrence of the first reported chest pain accompanied by ST deviation.</p> <p>Results</p> <p>By application of the above equation in log-log representation, the fitting procedure produced the following overall coefficients: Average <it>β </it>= 0.46, with a maximum = 0.62 and a minimum = 0.42; Average <it>δ </it>= 1.28, with a maximum = 1.79 and a minimum = 0.92. For a 2 mm ST-deviation, the full range of predicted ventricular fibrillation probability extended from about 13% at 1 month up to 86% at 4 years after the original cardiac event.</p> <p>Conclusions</p> <p>These results, at least preliminarily, appear acceptable and still call for full clinical test. The model seems promising, especially if other parameters were taken into account, such as blood cardiac enzyme concentrations, ischemic or infarcted epicardial areas or ejection fraction. It is concluded, considering these results and a few references found in the literature, that the allometric model shows good predictive practical value to aid medical decisions.</p