Military Institute of Health Service

Warsaw, Poland

Military Institute of Health Service

Warsaw, Poland
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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.


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.


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.


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.


Dobrowolski A.P.,Military University of Technology | Wierzbowski M.,Military University of Technology | Tomczykiewicz K.,Military Institute of Health Service
Computer Methods and Programs in Biomedicine | Year: 2012

This paper describes a new method for the classification of neuromuscular disorders based on the analysis of scalograms determined by the Symlet 4 wavelet technique. The approach involves isolating single motor unit action potentials (MUAPs), computing their scalograms, taking the maximum values of the scalograms in five selected scales, and averaging across MUAPs to give a single 5-dimensional feature vector per subject. After SVM analysis, the vector is reduced to a single decision parameter, called the Wavelet Index, allowing the subject to be assigned to one of three groups: myogenic, neurogenic or normal. The software implementation of the method described above created a tool supporting electromyographic (EMG) examinations. The method is characterized by a high probability for the accurate diagnosis of muscle state. The method produced 5 misclassifications out of 800 examined cases (total error of 0.6%). © 2010 Elsevier Ireland Ltd.


Tichopad A.,R.Ø.S.A. | Roberts C.,Pfizer | Gembula I.,R.Ø.S.A. | Hajek P.,Pfizer | And 6 more authors.
PLoS ONE | Year: 2013

We estimate and describe the incidence rates, mortality, and cost of CAP (community-acquired pneumonia), in both inpatient and outpatient settings, in the Czech Republic (CZ), Slovakia (SK), Poland (PL), and Hungary (HU). A retrospective analysis was conducted on administrative data from the health ministry and insurance reimbursement claims with a primary diagnosis of pneumonia in 2009 to determine hospitalization rates, costs, and mortality in adults ≥50 years of age. Patient chart reviews were conducted to estimate the number of outpatient cases. Among all adults ≥50 years, the incidence of hospitalized CAP per 100,000 person years was: 456.6 (CZ), 504.6 (SK), 363.9 (PL), and 845.3 (HU). The average fatality rate for all adults ≥50 is 19.1%, and for each country; 21.7% (CZ), 20.9% (SK), 18.6% (PL), 17.8% (HU). Incidence, fatality, and likelihood of hospitalization increased with advancing age. Total healthcare costs of CAP in EUR was 12,579,543 (CZ); 9,160,774 (SK); 22,409,085 (PL); and 18,298,449 (HU); with hospitalization representing over 90% of the direct costs of treatment. The burden of CAP increases with advancing age in four CEE countries, with hospitalizations driving the costs of CAP upwards in the elderly population. Mortality rates are generally higher than reported in Western EU countries. © 2013 Tichopad et al.


Targowski T.,Military Institute of Health Service | Jahnz-Rozyk K.,Military Institute of Health Service | Owczarek W.,Military Institute of Health Service | Raczka A.,Military Institute of Health Service | And 3 more authors.
Respiratory Medicine | Year: 2010

Purpose: Evaluation of relationships between survival time of patients with advanced, non-resectable non-small cell lung cancer (NSCLC) and telomerase activity in aspirates, collected from primary lung tumours, and serum p53 protein levels. Material and methods: The study group consisted of 52 patients with advanced (stage IIIB and IV) non-small cell lung cancer. In all of them, transthoracic fine-needle biopsy (TFNB) of focal pulmonary lesion was performed. The aspirates were subjected to telomerase activity by the PCR-ELISA PLUS method and serum levels of p53 protein were determined by the ELISA method. Additionally, clinical advancement of cancer and the time period of survival were assessed in the studied group. Kaplan-Meyer method and Cox analysis were used for statistical evaluation of survival prognosis. Results: Increased telomerase activity was observed in 42 (81%) of the patients with non-resectable non-small cell lung cancer. Elevated concentrations of serum p53 protein were found in 28 (54%) of the participants. The following death rates were noted during the entire study period: twenty-three (23) (62%), out of 37 patients with increased telomerase activity, 7 (47%), out of 15 without detectable telomerase activity in primary lung tumour, 16 (57%), out of 28 subjects with increased serum levels of p53 protein and 14 (58%), out of 24 with no increased serum levels of p53. A significant relationship was observed in Cox hazard analysis between the time of survival and telomerase activity, while no such relationship was observed between the survival time period and serum p53 protein levels or sex, age, primary lung tumour size, lymph node status or development of distant metastases. Conclusion: Telomerase activity in advanced primary non-small cell lung cancer is a better predictor of patients' survival than serum levels of p53 protein. The assessment of telomerase activity supplements in the prognosis of survival in the course of non-resectable NSCLC. © 2010 Elsevier Ltd. All rights reserved.


PubMed | Military Institute of Health Service
Type: Journal Article | Journal: Respiratory medicine | Year: 2010

Evaluation of relationships between survival time of patients with advanced, non-resectable non-small cell lung cancer (NSCLC) and telomerase activity in aspirates, collected from primary lung tumours, and serum p53 protein levels.The study group consisted of 52 patients with advanced (stage IIIB and IV) non-small cell lung cancer. In all of them, transthoracic fine-needle biopsy (TFNB) of focal pulmonary lesion was performed. The aspirates were subjected to telomerase activity by the PCR-ELISA PLUS method and serum levels of p53 protein were determined by the ELISA method. Additionally, clinical advancement of cancer and the time period of survival were assessed in the studied group. Kaplan-Meyer method and Cox analysis were used for statistical evaluation of survival prognosis.Increased telomerase activity was observed in 42 (81%) of the patients with non-resectable non-small cell lung cancer. Elevated concentrations of serum p53 protein were found in 28 (54%) of the participants. The following death rates were noted during the entire study period: twenty-three (23) (62%), out of 37 patients with increased telomerase activity, 7 (47%), out of 15 without detectable telomerase activity in primary lung tumour, 16 (57%), out of 28 subjects with increased serum levels of p53 protein and 14 (58%), out of 24 with no increased serum levels of p53. A significant relationship was observed in Cox hazard analysis between the time of survival and telomerase activity, while no such relationship was observed between the survival time period and serum p53 protein levels or sex, age, primary lung tumour size, lymph node status or development of distant metastases.Telomerase activity in advanced primary non-small cell lung cancer is a better predictor of patients survival than serum levels of p53 protein. The assessment of telomerase activity supplements in the prognosis of survival in the course of non-resectable NSCLC.


PubMed | Military Institute of Health Service
Type: Journal Article | Journal: Archives of medical science : AMS | Year: 2012

This report presents the case of a young female suffered for many years from type 1 diabetes, complicated by recurrent urinary tract infections and urosepsis with multiple abscesses which led to right nephrectomy in 2002. The patient was hospitalised in our Department in June 2009 because of urosepsis in the course of multiple left renal abscesses and subsequent acute renal failure requiring hemodialysis. A dramatic decision of removing the solitary kidney was taken, and patient was included in a long-term renal replacement therapy programme in our Centre as a preparation to kidney and pancreas transplantation.


PubMed | Military Institute of Health Service
Type: Journal Article | Journal: Muscle & nerve | Year: 2012

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.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.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.This proposed approach provides a sensitive and reliable method for evaluating and characterizing MUAPs.

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