Wyniki wyszukiwania - BazTech

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Feature vector or time-series – comparison of gestures representations in automatic gesture recognition systems

Barczewska K., Wójtowicz W., Moszkowski T.

Challenges of Modern Technology

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2015

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Vol. 6, no. 1

1--5

EN

In this paper, we performed recognition of isolated sign language gestures - obtained from Australian Sign Language Database (AUSLAN) – using statistics to reduce dimensionality and neural networks to recognize patterns. We designated a set of 70 signal features to represent each gesture as a feature vector instead of a time series, used principal component analysis (PCA) and independent component analysis (ICA) to reduce dimensionality and indicate the features most relevant for gesture detection. To classify the vectors a feedforward neural network was used. The resulting accuracy of detection ranged between 61 to 87%.

2

Flow analysis within mechanical heart valve - medtronic hall - and validation of results by numerical modelling

Moszkowski T., Jaworek M., Kostrzewa B., Lalik K., Darłak M., Altyntsev I., Kustosz R.

Journal of Medical Informatics & Technologies

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2011

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Vol. 17

295--302

EN

Research was conducted to analyze the flow of a fluid within mechanical heart valve - Medtronic Hall. Physical experiment and numerical modelling were performed. The aim of the research was to determine the difference between obtained experimental and numerical data. In the experiment a dependency between static flow rate within the valve and static inlet and outlet pressure in the valve duct was examined. Moreover a dependency between static flow rate and angular valve position was also determined. Experimental data was used to perform a numerical flow analysis. The obtained flow rate values and angular positions of the valve were set to a finite-volumes-method model in order to achieve model output pressure values identical or similar to the ones obtained from the experiment. The resulting pressure values from the experiment and numerical analyses proved to be of the same order of magnitude, varying only by up to 10%. However, as far as differential pressure is concerned, numerical results were out of the range of measurement resolution. It can be assumed that numerical flow analyses quite correctly predict the real phenomenon and in view of measurement inaccuracy of used sensors authors would suggest using more accurate ones and repeating measurements for future clarification.

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Możliwości wykorzystania sygnału EMG do sterowania

Nawrocka A., Moszkowski T., Szefer P.

Aktualne Problemy Biomechaniki

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2011

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z. 5

109--114

PL

Celem przeprowadzonych badań było wykazanie użyteczności sygnału EMG (elektromiograficznego) w teorii sterowania. Przeprowadzono badanie stwierdzające powiązanie pomiędzy aktywnością elektryczną mięśni (biceps i triceps brachii) a siłą mięśniową w warunkach statycznych. Opracowano algorytm obróbki danych elektromiograficznych. Wykazano liniową zależność pomiędzy omawianymi wielkościami fizycznymi jednocześnie potwierdzając użyteczność sygnału EMG jako sygnału sterującego. Jednakże zaleca się poszerzenie przeprowadzonych badań o badania dynamiczne skurczu mięśnia.

EN

The aim of the study was to perform sEMG (surfacial electromyography) signal analysis focusing on its applicability for control purposes. Research that aimed at determining the relation between electromuscular activity and static muscular force was conducted. Algorithm for processing of the obtained data was prepared. Linear dependence of the aforementioned quantities was established, therefore the convenience of usage of sEMG as a control signal was confirmed. However, further research on the dynamics of muscular contraction is necessary.