Publications by authors named "Maria Bienkowska"

Pain assessment in patients with temporomandibular joint (TMJ) disorders during physiotherapy is a challenging yet desired task. Our study addresses two issues. First, we compare the pain perception in patients with TMJ disorders and a control group.

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Access to large amounts of data is essential for successful machine learning research. However, there is insufficient data for many applications, as data collection is often challenging and time-consuming. The same applies to automated pain recognition, where algorithms aim to learn associations between a level of pain and behavioural or physiological responses.

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This study aims to design a time-continuous pain level assessment system for temporomandibular joint therapy. Our objectives cover verifying literature suggestions on pain stimulus, protocols for collecting reference data, and continuous pain recognition models. We use two types of pain data acquired during 1) heat stimulation and 2) temporomandibular joint therapy.

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The study aims to present the results of paper compression under an axial load. Different heights of samples subjected to compression were taken into account. The main goal of the analysis was to determine experimentally the maximum compression load.

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The main objective of the presented research was to find a model that describes the maximum compressive force of paper in its plane. The research began with crushing tests of a number of packaging paper samples of various lengths. It was shown that due to the specific structure of the paper and the high heterogeneity of its structure, packaging paper is material where it is difficult to determine the maximum compressive stress.

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This paper concerns the analysis of five-layer corrugated paperboard subjected to a four-point bending test. The segment of paperboard was tested to determine the bending stiffness. The investigations were conducted experimentally and numerically.

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In this paper, a method for evaluating the chronological age of adolescents on the basis of their voice signal is presented. For every examined child, the vowels a, e, i, o and u were recorded in extended phonation. Sixty voice parameters were extracted from each recording.

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The popularization of acoustic stimulation during the prenatal period encourages the analysis of sounds reaching the inside of the uterus. To assess the distortion of any sound stimuli, a mathematical model of attenuation has to be used. In this paper a mathematical model is proposed on the basis of data from a physical model.

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A method for evaluating the menarcheal status of girls on the basis of their voice features is presented in the paper. The registration procedure consists of voice recording and measuring 20 anthropological features. The input feature vector is a combination of voice and anthropometric parameters, counting 220 features.

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