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Search results for: wavelet transforms
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Experimental study on ultrasonic monitoring of splitting failure in reinforced concrete
PublicationThis paper investigates inspection of reinforced concrete elements sensitive to the splitting failure. The behaviour of a reinforced concrete specimen subjected to a tensile stress is considered. The damage detection procedure is based on the ultrasonic wave propagation technique. The piezoelectric transducers are located on both ends of the specimen and the measurements are taken periodically during the incrementally increased...
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Coupling of Blood Pressure and Subarachnoid Space Oscillations at Cardiac Frequency Evoked by Handgrip and Cold Tests: A Bispectral Analysis
PublicationThe aim of the study was to assess blood pressure–subarachnoid space (BP–SAS) width coupling properties using time–frequency bispectral analysis based on wavelet transforms during handgrip and cold tests. The experiments were performed on a group of 16 healthy subjects (F/M; 7/9) of the mean age 27.2 ± 6.8 years and body mass index of 23.8 ± 4.1 kg/m². The sequence of challenges was first handgrip and then cold test. The handgrip...
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Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in noisy environment
PublicationThe main obstacle in development of intelligent autodiagnosis medical systems based on the analysis of phonocardiography (PCG) signals is noise. The noise can be caused by digestive and respiration sounds, movements or even signals from the surrounding environment and it is characterized by wide frequency and intensity spectrum. This spectrum overlaps the heart tones spectrum, which makes the problem of PCG signal filtrating complex....
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Arm EMG Wavelet-Based Denoising System
PublicationThese paper presents research results of muscle EMG signal denoising. In the same time two muscles were examined - an adductor muscle (biceps brachii) and an abductor muscle (tricpeps brachii). The EMG signal was filtered using the wavelet transform technique, having selected the crucial parameters as: wavelet basis function (Daubechies 4), 10 th decomposition level, threshold selection algorithm (Heurestic) and a sln rescaling...
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Monika Zamłyńska
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