The paper describes measurement and calculation of 2D distribution of the vibration signal originated by the gradient coil system of the magnetic resonance imaging (MRI) equipment. The measurement experiments were performed at the bottom plastic holder of the scanning area of the open-air weak magnetic field MRI device. Selection of a usable type of a vibration sensor for measurement in a magnetic field with low B0 up to 0.2 T is also discussed. Realized calibration of the chosen sensor (sensitivity and frequency response) together with determination of the propagation time delay between the excitation impulses and the subsequently generated vibration signal is mentioned, too. The picked-up vibration signal exhibits harmonic character so it is suitable to describe it by determined spectral properties and features. Obtained statistical results of spectral analysis will be used to improve image sharpening and reduction of the motion effect in the MR pictures of thin layer samples and phantoms scanned by this MRI system.

The paper deals with the photoplethysmographic (PPG) optical sensor usage for noninvasive acquisition of vital information about the cardiovascular system from different parts of the human skin surface. Finger-ring and ear-clip realizations of the transmission-type PPG sensor were tested first. For next PPG signal recording, the reflection PPG sensor was placed on fingers and on a wrist. PPG signal properties were described by energetic and temporal parameters and their statistical parameters together with determined instantaneous heart rate values. Our final aim was to find conditions, limitations, and recommendations for development of a wearable PPG sensor working in a magnetic field environment.

The paper describes an experiment with using the Gaussian mixture models (GMM) for automatic classification of the speaker age and gender. It analyses and compares the influence of different number of mixtures and different types of speech features used for GMM gender/age classification. Dependence of the computational complexity on the number of used mixtures is also analysed. Finally, the GMM classification accuracy is compared with the output of the conventional listening tests. The results of these objective and subjective evaluations are in correspondence.K e y w o r d s: GMM classifier, spectral and prosodic features of speech, speaker gender and age classification

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