• Keywords
• společnost Artmedic, Pelvic seat, Intimee, Medlander Pelvic,
• MeSH
• Biomedical Technology * methods   MeSH
• Electric Stimulation methods   instrumentation   MeSH
• Electromagnetic Fields MeSH
• Urinary Incontinence * surgery   diagnosis   drug therapy   rehabilitation   MeSH
• Low-Level Light Therapy MeSH
• Humans MeSH
• Healthy Lifestyle MeSH
• Check Tag
• Humans MeSH

• MeSH
• Biomedical Technology * classification   methods   MeSH
• Contact Lenses * trends   MeSH
• Permeability MeSH
• Light MeSH

• Keywords
• inzulínová pumpa,
• MeSH
• Biomedical Technology methods   instrumentation   MeSH
• Diabetes Mellitus, Type 1 blood   prevention & control   MeSH
• Insulin Infusion Systems * classification   MeSH
• Continuous Glucose Monitoring methods   instrumentation   MeSH
• Humans MeSH
• Patient Selection MeSH
• Check Tag
• Humans MeSH
• Publication type
• Review MeSH

• MeSH
• Biomedical Technology methods   instrumentation   statistics & numerical data   MeSH
• Diabetes Mellitus * prevention & control   therapy   MeSH
• Glycated Hemoglobin analysis   MeSH
• Insulin, Regular, Human administration & dosage   MeSH
• Insulin Infusion Systems statistics & numerical data   MeSH
• Communication MeSH
• Blood Glucose analysis   MeSH
• Humans MeSH
• Statistics as Topic MeSH
• Telemedicine * methods   organization & administration   instrumentation   statistics & numerical data   MeSH
• Patient Education as Topic MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

• MeSH
• Treatment Adherence and Compliance MeSH
• Algorithms MeSH
• Biomedical Technology classification   methods   instrumentation   trends   MeSH
• Diabetes Mellitus, Type 1 * prevention & control   therapy   MeSH
• Insulin, Regular, Human administration & dosage   MeSH
• Insulin Infusion Systems MeSH
• Blood Glucose analysis   MeSH
• Humans MeSH
• Patient Preference MeSH
• Patient Education as Topic MeSH
• Check Tag
• Humans MeSH
• Publication type
• Review MeSH

Zubní kaz je chronické multifaktoriální onemocnění, které postihuje značnou část světové populace. Jeho etiologie je komplexní a zahrnuje interakci mikrobiálních, genetických, biochemických, sociálních a behaviorálních faktorů. Projekt je koncipován jako kombinace prospektivního sledování vybrané kohorty a průřezových studií [dětí s kazem vs. zdravých kontrol nebo dětí s kazem raného dětství (ECC)] a in vitro studií, které se budou zabývat (i) in vitro kultivací kariogenních bakteriálních kmenů za přítomnosti substrátů s různým kariogenním potenciálem, (ii) analýzou jejich transkriptomu/metabolomu, (iii) multivariační analýzou klinických, biochemických, mikrobiálních, genetických faktorů a vlivů zevního prostředí a (iv) edukací matek dětí – behaviorální intervencí. Začlenění získaných poznatků do praxe by mohlo přispět k redukci nákladů na zdravotní péči související s léčbou kazu. Zhodnocení individuálního rizika rozvoje kazu by umožnilo přechod k “personalizované medicíně“ (zejména v rámci diagnostiky a prevence onemocnění).; Dental caries, a chronic multifactorial disease, is a major oral health problem worldwide. Its etiology involves a complex interplay of microbial, genetic, biochemical, social, physical environmental, and health-influencing behavioral factors. The project is designed as a combination of prospective monitoring of selected cohort and a cross-sectional studies [children with caries vs. healthy controls or children with early childhood caries (ECC)], and in vitro studies addressing (i) in vitro cultivation of cariogenic bacterial strains in the presence of substrates with various cariogenic potential, (ii) their transriptome/metabolome analysis, (iii) multivariate analyses of clinical, biochemical, microbial, genetic and environmental factors, and (iv) education of mothers and children–behavioral intervention. Implementation of obtained knowledge might reduce costs on health care in connection with caries. The assessment of the individual risk could rationalize health care in terms of "personalized medicine" (particularly the disease diagnosis and prevention).

• MeSH
• Bacteriological Techniques MeSH
• Biomedical Technology methods   MeSH
• Child MeSH
• Cariogenic Agents adverse effects   MeSH
• Cohort Studies MeSH
• Culture Techniques methods   MeSH
• Humans MeSH
• Metabolome MeSH
• Metabolomics methods   MeSH
• Cross-Sectional Studies MeSH
• Gene Expression Profiling methods   MeSH
• Health Education, Dental methods   MeSH
• Dental Caries diagnosis   etiology   prevention & control   MeSH
• Check Tag
• Child MeSH
• Humans MeSH

• Conspectus
• Stomatologie
• NML Fields
• zubní lékařství
• biomedicínské inženýrství
• preventivní medicína
• NML Publication type
• závěrečné zprávy o řešení grantu AZV MZ ČR

In this paper, we describe a technical design of wearable multi-sensor systems for physiological data measurement and wide medical applications, significantly impacted in telehealth. The monitors are composed of three analog front-end (AFE) devices, which assist with interfacing digital electronics to the noise-, time-sensitive physiological sensors for measuring ECG (heart-rate monitor), RR (respiration-rate monitor), SRL (skin resistivity monitor). These three types of sensors can be used separately or together and allow to determine a number of parameters for the assessment of mental and physical condition. The system is designed based on requirements for demanding environments even outside the realm of medical applications, and in accordance with Health and Safety at Work directives (89/391/CE and Seveso-II 96/82/EC) for occupational hygiene, medical, rehabilitation, sports and fitness applications.

• MeSH
• Electronic Data Processing methods   instrumentation   MeSH
• Biomedical Technology methods   instrumentation   MeSH
• Biomedical Research MeSH
• Respiratory Rate MeSH
• Mental Health MeSH
• Electrocardiography methods   instrumentation   MeSH
• Humans MeSH
• Wearable Electronic Devices * classification   MeSH
• Heart Rate MeSH
• Telemedicine methods   instrumentation   MeSH
• Physical Fitness MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

The standard ISO 81060–2:2018 allows the use of invasive blood pressure monitoring systems as reference gauges in clinical trials of automated non-invasive automated sphygmomanometers. The reference measuring system is subject to requirements for a maximum permissible error of ±2 mmHg, and the resonant frequency and damping coefficient must also be characterized. The 'catheter-sensor' system used in clinical practice only has defined parameters required by the standard for the chamber with the pressure sensor. The characteristic parameters of the whole measuring system cannot be defined even when the type of catheter used is known, because after every irrigation the system changes the values of its natural frequency (fn) and damping ratio (ζ). These parameters directly define the frequency response of the system, its resonant frequency and the damping coefficient. The characteristic parameters of the 'catheter-sensor' system were defined on the basis of an analysis of a second-order linear model and the measurement of the step response of the real system. Measurements have shown that repeated irrigation of the same 'catheter-sensor' system can change the value of the system’s natural frequency by tens of Hz. In well-irrigated systems, the accuracy required by the standard was met. The following values were determined for this system: fn = 38.8 Hz and ζ = 0.130. In the second case, when the system was probably affected by air bubble compliancy, the measurement accuracy was much lower. The discovered deviation was tens of mmHg. This system had fn = 6.5 Hz a ζ = 0.281.

• MeSH
• Biomedical Technology methods   MeSH
• Biomedical Research instrumentation   MeSH
• Catheters classification   trends   MeSH
• Blood Pressure Determination * methods   instrumentation   MeSH
• Blood Pressure Monitors classification   trends   MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

An interface based on electromyographic (EMG) signals is considered one of the central fields in human-machine interface (HCI) research with broad practical use. This paper presents the recognition of 13 individual finger movements based on the time-frequency representation of EMG signals via spectrograms. A deep learning algorithm, namely a convolutional neural network (CNN), is used to extract features and classify them. Two approaches to EMG data representations are investigated: different window segmentation lengths and reduction of the measured channels. The overall highest accuracy of the classification reaches 95.5% for a segment length of 300 ms. The average accuracy attains more than 90% by reducing channels from four to three.

• MeSH
• Biomedical Technology methods   instrumentation   MeSH
• Biomedical Research MeSH
• Electromyography * methods   instrumentation   MeSH
• Humans MeSH
• Signal Processing, Computer-Assisted instrumentation   MeSH
• Fingers diagnostic imaging   innervation   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

The goal of the study was to design a model of cardiac ventricles with realistic geometry that enables simulation of the ventricular activation with normal conduction system functions, as well as with bundle branch blocks. In ventricles, electrical activation propagates from the His bundle to the left and right bundle branches and continues to the fascicles and branching fibers of the Purkinje system. The role of these parts of the conduction system is to lead the activation rapidly and synchronously to the left and right ventricle. The velocity of propagation in the conduction system is several times higher than in the surrounding ventricular myocardium. If the conduction system works normally, QRS duration representing the total activation time of the ventricles lies in the physiological range of about 80 to 120 ms but it is more than 120 ms in the case of bundle branch blocks. In our study, the realistic geometry of the ventricles was constructed on the base of a patient CT scan, defining epicardial and endocardial surfaces. The first part of the conduction system (fast-conducting bundle branches, fascicles in the left ventricle and initial parts of the Purkinje fibers) was modeled as polyline pathways isolated from the surrounding ventricular tissue. The remaining part of the Purkinje system was modeled as an endocardial layer with higher conduction velocity. The propagation of the electrical activation in the ventricular model was modeled using reaction-diffusion (RD) equations, except for the first part of the conduction system, where the activation times were evaluated algebraically with respect to predefined velocity of propagation and estimated distance between the His bundle and particular entry point to the layer with higher conduction velocity. Propagation of activation in cardiac ventricles was numerically solved in Comsol Multiphysics environment. Several configurations of the first part of the conduction system with different number of polyline pathways and entry points were proposed and tested to achieve realistic activation propagation. For the model with 9 starting points, realistic total activation time (TAT) of the whole ventricles of about 108 ms was obtained for the model with normal conduction system, and realistic TAT of 126 ms and 149 ms were obtained for the right and left bundle branch block (RBBB, LBBB), respectively. Very similar TAT was found also for the model with 7 starting points, but unrealistically long TAT was obtained in LBBB simulation for the model with only 5 starting points.

• MeSH
• Models, Anatomic MeSH
• Biomedical Technology methods   MeSH
• Biomedical Research instrumentation   trends   MeSH
• Bundle-Branch Block * diagnostic imaging   physiopathology   MeSH
• Humans MeSH
• Models, Cardiovascular MeSH
• Computer Simulation classification   MeSH
• Heart Ventricles anatomy & histology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH