ABSTRACT
A heart rate biofeedback system consisting of a JPR 12 minicomputer (12 bit, 4 K), of input devices (an electronic circuit triggered by the EEG R-waves or a photoelectric ear lobe pulse detector and of output devices (a feedback indicator of successful or unsuccessful heart rate control during the preceding time interval, the teletype and the paper tape punch) is described. The actual heart rate is measured and compared with levels differing from the average by a preselected number of pulses/min. When a preset criterion is met, the levels are shifted automatically. In control session shuffled data from the preceding experimental session are used for feedback.
Subject(s)
Biofeedback, Psychology/physiology , Heart Rate , Humans , Psychophysiology/instrumentationABSTRACT
Some examples of the use of the principal component model for the economic description of the structure of the multiple time series and for the data reduction in the quantitative EEG studies are presented. The broad-band EEG frequency spectra were measured with the use of an electronic system designed by J. Dvorák. The EEG spectral power densities were computed via the discrete Fourier Transform (namely FFT) algorithm. The estimated two or three first principal components account for the major part of the total variance of individual EEG variables: The results hold for the used elementary epoch of measurement, i.e. 5 sec. - With the use of the algorithms and FORTRAN IV programs developed by J. Andel, T. Cipra and L. Tomásek a data reduction by a factor of 1:2000 can be achieved without any substantial loss of biological information. - The described methods help to obtain a better insight into the structure of the data and represent a powerful tool for data reduction at least in a certain class of experimental EEG studies (experimental toxicology, pharmacology, experimental neurology).
