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Ostrowiec Świętokrzyski, Poland

Tomczykiewicz K.,Military Institute of Health Service | Dobrowolski A.P.,Military University of Technology | Wierzbowski M.,Military University of Technology
Muscle and Nerve | Year: 2012

Introduction: Electrophysiological studies of human motor units can use various electromyographic techniques. Together with the development of new techniques for analysis and processing of bioelectric signals, motor unit action potential (MUAP) wavelet analysis represents an important change in the development of electromyographic techniques. Methods: The proposed approach involves isolating single MUAPs, computing their scalograms, taking the maximum values of the scalograms in 5 selected scales, and averaging across MUAPs to give a single five-dimensional feature vector per muscle. After Support Vector Machine analysis, the feature vector is reduced to a single decision parameter that allows the subject to be assigned to 1 of 3 groups: myogenic, healthy, or neurogenic. The software is available as freeware. Results: MUAP wavelet analysis yielded consistent results for the diagnostic index and muscle classification, with only 7 incorrect classifications out of a total of 1,015 samples. Conclusions: This proposed approach provides a sensitive and reliable method for evaluating and characterizing MUAPs. © 2012 Wiley Periodicals, Inc. Source

Dobrowolski A.P.,Military University of Technology | Wierzbowski M.,Military University of Technology | Tomczykiewicz K.,Military Institute of Health Service
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 | Year: 2010

The paper presents a new method for neuromuscular disorders diagnosis based on analysis of scalograms determined by the Symlet 4 wavelets technique. Obtained results served for extraction of five features, which, after SVM analysis, were reduced to a single decision parameter allowing assigning the investigated cases to one of three groups: myogenic, neurogenic or normal. Software implementation of the method permitted to create a diagnostic tool for EMG investigation aid. The method characterizes high probability of accurate diagnosis of a muscle state with total error of 0.5% - 4 misclassifications out of 780 examined cases. © 2010 IEEE. Source

Wojtowicz B.,Military University of Technology | Dobrowolski A.,Military University of Technology | Tomczykiewicz K.,Military Institute of Health Service
Metrology and Measurement Systems | Year: 2015

This paper presents the design process and the results of a novel fall detector designed and constructed at the Faculty of Electronics, Military University of Technology. High sensitivity and low false alarm rates were achieved by using four independent sensors of varying physical quantities and sophisticated methods of signal processing and data mining. The manuscript discusses the study background, hardware development, alternative algorithms used for the sensor data processing and fusion for identification of the most efficient solution and the final results from testing the Android application on smartphone. The test was performed in four 6-h sessions (two sessions with female participants at the age of 28 years, one session with male participants aged 28 years and one involving a man at the age of 49 years) and showed correct detection of all 40 simulated falls with only three false alarms. Our results confirmed the sensitivity of the proposed algorithm to be 100% with a nominal false alarm rate (one false alarm per 8 h). © 2015 Polish Academy of Sciences. All rights reserved. Source

Czerwinska K.,Institute of Cardiology | Orlowska-Baranowska E.,Institute of Cardiology | Witkowski A.,Institute of Cardiology | Demkow M.,Institute of Cardiology | And 7 more authors.
Archives of Medical Science | Year: 2011

Surgical aortic valve replacement (AVR) still remains the treatment of choice in symptomatic significant aortic stenosis (AS). Due to technical problems, extensive calcification of the ascending aorta ("porcelain aorta") is an additional risk factor for surgery and transapical aortic valve implantation (TAAVI) is likely to be the only rescue procedure for this group of patients. We describe the case of an 81-year-old woman with severe AS and "porcelain aorta", in whom the only available life-saving intervention was TAAVI. Copyright © 2011 Termedia & Banach. Source

Dobrowolski A.,Military University of Technology | Suchocki M.,Military University of Technology | Tomczykiewicz K.,Military Institute of Health Service | Majda-Zdancewicz E.,Military University of Technology
Biocybernetics and Biomedical Engineering | Year: 2016

In electrophysiological hearing assessment and diagnosis of brain stem lesions are most often used auditory brainstem evoked potentials of short latency. They are characterized by successively arranged maxima as a function of time, called waves. Morphology of the course, in particular, the timing and amplitude of each wave, allow neurologist diagnosis, which is not an easy task. Neurologist requires experience, attention and very good perception. In order to support the diagnostic process, the authors have developed an algorithm implementing the automated classification of auditory evoked potentials to the group of pathological and physiological cases. The sensitivity and specificity of group numbering of 130 cases are respectively 95% and 98% and classification accuracy is equal to 97%. The procedures developed by the authors for generation of distinctive features based on wavelet decomposition with a SVM network-based classifier have been integrated into a diagnostic application directly interoperable with Nicolet Viking Select (Natus Medical Inc., USA) system data files. © 2016 Nałȩcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier Sp. z o.o. All rights reserved. Source

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