The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure sensors, or other sensors, which may provide more efficient patient bed monitoring results. This work also covers the aspects of interference occurrence in the above-mentioned signals and sleep quality monitoring, which play a very important role in the analysis of biomedical signals and the choice of appropriate signal-processing methods. The provided information will help various researchers to understand the importance of vital sign monitoring and will be a thorough and up-to-date summary of these methods. It will also be a foundation for further enhancement of these methods.

• Klíčová slova
• biosignals, digital signal processing, sensors, vital sign monitoring,
• MeSH
• lidé MeSH
• lůžka * MeSH
• monitorování fyziologických funkcí přístrojové vybavení   metody   MeSH
• počítačové zpracování signálu MeSH
• spánek fyziologie   MeSH
• vitální znaky * fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Fetal alcohol spectrum disorders (FASD) are spectrum of neurodevelopmental conditions associated with prenatal alcohol exposure. The FASD manifests mostly with facial dysmorphism, prenatal and postnatal growth retardation, and selected birth defects (including central nervous system defects). Unrecognized and untreated FASD leads to severe disability in adulthood. The diagnosis of FASD is based on clinical criteria and neither biomarkers nor imaging tests can be used in order to confirm the diagnosis. The quantitative electroencephalography (QEEG) is a type of EEG analysis, which involves the use of mathematical algorithms, and which has brought new possibilities of EEG signal evaluation, among the other things-the analysis of a specific frequency band. The main objective of this study was to identify characteristic patterns in QEEG among individuals affected with FASD. This study was of a pilot prospective study character with experimental group consisting of patients with newly diagnosed FASD and of the control group consisting of children with gastroenterological issues. The EEG recordings of both groups were obtained, than analyzed using a commercial QEEG module. As a results we were able to establish the dominance of the alpha rhythm over the beta rhythm in FASD-participants compared to those from the control group, mostly in frontal and temporal regions. Second important finding is an increased theta/beta ratio among patients with FASD. These findings are consistent with the current knowledge on the pathological processes resulting from the prenatal alcohol exposure. The obtained results and conclusions were promising, however, further research is necessary (and planned) in order to validate the use of QEEG tools in FASD diagnostics.

• MeSH
• dítě MeSH
• dospělí MeSH
• elektroencefalografie MeSH
• epilepsie * patologie   MeSH
• lidé MeSH
• mozek patologie   MeSH
• prospektivní studie MeSH
• spektrum vrozených alkoholových poruch * diagnóza   patologie   MeSH
• těhotenství MeSH
• zpožděný efekt prenatální expozice * patologie   MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• lidé MeSH
• těhotenství MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

As it was mentioned in the previous part of this work (Part I)-the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their increasing usage in current clinical practice. In this paper, which is a Part II work-various innovative methods for the analysis of brain bioelectrical signals were presented and compared. It also describes both classical and advanced approaches for noise contamination removal such as among the others digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation, and wavelet transform.

• Klíčová slova
• bioelectrical signals, brain signals, electrocorticography, electroencephalography, signal processing methods,
• MeSH
• mozek MeSH
• počítačové zpracování signálu * MeSH
• vlnková analýza * MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).

• Klíčová slova
• biomedical signals, electrogastrography, electrohysterography, electromyography, electroneurography, electrooculography, electroretinography, signal processing,
• MeSH
• elektromyografie MeSH
• elektrookulografie MeSH
• elektroretinografie * MeSH
• počítačové zpracování signálu * MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Off-the-shelf, consumer-grade EEG equipment is nowadays becoming the first-choice equipment for many scientists when it comes to recording brain waves for research purposes. On one hand, this is perfectly understandable due to its availability and relatively low cost (especially in comparison to some clinical-level EEG devices), but, on the other hand, quality of the recorded signals is gradually increasing and reaching levels that were offered just a few years ago by much more expensive devices used in medicine for diagnostic purposes. In many cases, a well-designed filter and/or a well-thought signal acquisition method improve the signal quality to the level that it becomes good enough to become subject of further analysis allowing to formulate some valid scientific theories and draw far-fetched conclusions related to human brain operation. In this paper, we propose a smoothing filter based upon the Savitzky-Golay filter for the purpose of EEG signal filtering. Additionally, we provide a summary and comparison of the applied filter to some other approaches to EEG data filtering. All the analyzed signals were acquired from subjects performing visually involving high-concentration tasks with audio stimuli using Emotiv EPOC Flex equipment.

• Klíčová slova
• Brain-Computer Interfaces, Emotiv Flex, digital filtering, electroencephalography, signal processing,
• Publikační typ
• časopisecké články MeSH

Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

• Klíčová slova
• Brain-Computer Interfaces, electrocorticography, electroencephalography, neuro-imaging, signal processing methods,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.

• Klíčová slova
• ballistocardiography, car seats, electrocardiography, electroencephalography, seismocardiography, sensors, signal processing, vital sign monitoring,
• MeSH
• automobily * MeSH
• balistokardiografie * MeSH
• dětské zádržné systémy * MeSH
• elektrokardiografie * MeSH
• lidé MeSH
• počítačové zpracování signálu MeSH
• srdeční frekvence MeSH
• vitální znaky * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH