The article discusses a new method for the pulse wave velocity estimation using a pneumatic blood pressure sensor previously developed by the authors and the capability of that method for the early atherosclerosis diagnosis. The method proposed is based on measuring by the pneumatic sensor of the so-called pulse transit time - the time delay between the pulse wave signal and the synchronous ECG record. The article substantiates the way of determining, according to the waveform of the pulse signal, of that front characteristic time moment, which is more reliable for the measuring the delay to the R-peak of an ECG. The issues of accounting the variability of the pulse wave front delay at different points of the artery in the calculating the mean value and standard deviation of the pulse wave propagation velocity are discussed in detail. Almost all discussed features of the proposed methodology are illustrated by experimental data.

The development of the third-generation devices for medical home care systems is in the center of discussion. The results of developing non-invasive arterial pressure monitoring channel on the basis of the unique pneumatic sensor are discussed in detail. In particular, the main principles of operation, design features and testing results of a pneumatic sensor are considered. Namely, the issues of the stable air flow regime in the sensor's working chamber are discussed. It is shown that the miniature size of the sensor and the possibility of its precise positioning directly in the measurement zone on small (< 1 mm) areas of the skin elastic surfaces result in improved quality of pulse wave shape recovery, the parameters continuity measured and the disturbances reduction. Measurement examples for some human superficial arteries are given. The possibility of continuous measurement of the actual value of blood pressure for radial and temporal arteries is confirmed.

The report is devoted to computer analysis of long-term EEG records. The visual review of such big data requires a lot of time and is not always unbiased. That is why the search for efficient instruments of long-term EEG records processing is a task of utmost importance for neurologic analysis. To solve this problem, we developed a convenient instrument that expands a one-dimensional EEG signal into a two-dimensional representation. In contrast to the well-known time-frequency representations we choose for EEG-like signals another representation domain - the time-scale one. This is done because fragments of interest in the EEG signal - seizures, coma signals, alpha-spindles and others often represent a few repeating waveforms, whose spectra are obscure. The most effective here is the correlative-type analysis, a special form of which - the multi-scale correlative analysis is put forward as the basis for a novel representation. The paper discusses in detail the multi-scale correlation algorithm of the application developed and shows how the suggested functionality of the instrument is provided by the algorithmic features. The performance of the instrument is illustrated by the results of processing rats long-term EEG, in particular, before and after traumatic brain injury.