Szczepan Paszkiel – författare

This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology. In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.

This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology.

In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.

This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology. In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.

This book presents the proceedings of the 4th International Scientific Conference IC BCI 2021 Opole, Poland. The event was held at Opole University of Technology in Poland on 21 September 2021. Since 2014, the conference has taken place every two years at the University’s Faculty of Electrical Engineering, Automatic Control and Informatics. The conference focused on the issues relating to new trends in modern brain–computer interfaces (BCI) and control engineering, including neurobiology–neurosurgery, cognitive science–bioethics, biophysics–biochemistry, modeling–neuroinformatics, BCI technology, biomedical engineering, control and robotics, computer engineering and neurorehabilitation–biofeedback.

This book presents the proceedings of the 4th International Scientific Conference IC BCI 2021 Opole, Poland. The event was held at Opole University of Technology in Poland on 21 September 2021. Since 2014, the conference has taken place every two years at the University’s Faculty of Electrical Engineering, Automatic Control and Informatics. The conference focused on the issues relating to new trends in modern brain–computer interfaces (BCI) and control engineering, including neurobiology–neurosurgery, cognitive science–bioethics, biophysics–biochemistry, modeling–neuroinformatics, BCI technology, biomedical engineering, control and robotics, computer engineering and neurorehabilitation–biofeedback.

The BCI technology finds newer and newer implementations. Year by year, the number of publications in this field grows exponentially. This book attempts to describe the implementation of the brain-computer technology based on both STM32 and Arduino microcontrollers. In addition, the application of BCI technology in the field of intelligent houses, robotic lines as well as in the field of bionic prostheses was presented. One of the chapters of the monograph also discusses the issue of fMRI in the context of the possibility of analyzing images made as part of fMRI through solutions based on machine learning. A practical implementation of the TensorFlow framework was presented. The fMRI technique is also often implemented in BCI solutions. The conducted literature studies show that the technology of BCI is undoubtedly a technology of the future. However, there is a need for continuous development of biomedical signal processing methods in order to obtain the most efficient implementationsin the case of non-invasive implementation of BCI technology based on EEG. The further development of BCI technology has a huge impact on the techniques of rehabilitation of people with disabilities. Nowadays, wheelchairs are being constructed, thanks to which a disabled person is physically able to direct his position in a certain direction and at a certain speed. Thanks to BCI, it is also possible to create an individual speech synthesizer, with the help of which a paralyzed person will be able to communicate with the outside world. New limb prostheses that will replace the lost locomotor system in almost one hundred percent are still being developed. Some prostheses are connected to the human nervous system, thanks to which they are able to send feedback to our brain about the shape, hardness and temperature of the object held in the artificial limb.

The BCI technology finds newer and newer implementations. Year by year, the number of publications in this field grows exponentially. This book attempts to describe the implementation of the brain-computer technology based on both STM32 and Arduino microcontrollers. In addition, the application of BCI technology in the field of intelligent houses, robotic lines as well as in the field of bionic prostheses was presented. One of the chapters of the monograph also discusses the issue of fMRI in the context of the possibility of analyzing images made as part of fMRI through solutions based on machine learning. A practical implementation of the TensorFlow framework was presented. The fMRI technique is also often implemented in BCI solutions. The conducted literature studies show that the technology of BCI is undoubtedly a technology of the future. However, there is a need for continuous development of biomedical signal processing methods in order to obtain the most efficient implementationsin the case of non-invasive implementation of BCI technology based on EEG. The further development of BCI technology has a huge impact on the techniques of rehabilitation of people with disabilities. Nowadays, wheelchairs are being constructed, thanks to which a disabled person is physically able to direct his position in a certain direction and at a certain speed. Thanks to BCI, it is also possible to create an individual speech synthesizer, with the help of which a paralyzed person will be able to communicate with the outside world. New limb prostheses that will replace the lost locomotor system in almost one hundred percent are still being developed. Some prostheses are connected to the human nervous system, thanks to which they are able to send feedback to our brain about the shape, hardness and temperature of the object held in the artificial limb.

The BCI technology finds newer and newer implementations. Year by year, the number of publications in this field grows exponentially. This book attempts to describe the implementation of the brain-computer technology based on both STM32 and Arduino microcontrollers. In addition, the application of BCI technology in the field of intelligent houses, robotic lines as well as in the field of bionic prostheses was presented. One of the chapters of the monograph also discusses the issue of fMRI in the context of the possibility of analyzing images made as part of fMRI through solutions based on machine learning. A practical implementation of the TensorFlow framework was presented. The fMRI technique is also often implemented in BCI solutions. The conducted literature studies show that the technology of BCI is undoubtedly a technology of the future. However, there is a need for continuous development of biomedical signal processing methods in order to obtain the most efficient implementationsin the case of non-invasive implementation of BCI technology based on EEG. The further development of BCI technology has a huge impact on the techniques of rehabilitation of people with disabilities. Nowadays, wheelchairs are being constructed, thanks to which a disabled person is physically able to direct his position in a certain direction and at a certain speed. Thanks to BCI, it is also possible to create an individual speech synthesizer, with the help of which a paralyzed person will be able to communicate with the outside world. New limb prostheses that will replace the lost locomotor system in almost one hundred percent are still being developed. Some prostheses are connected to the human nervous system, thanks to which they are able to send feedback to our brain about the shape, hardness and temperature of the object held in the artificial limb.

This edition of the volume ‘Advances in Intelligent Systems and Computing’ presents the proceedings of the 3rd International Scientific Conference BCI. The event was held at Opole University of Technology in Poland on 13 and 14 March 2018. Since 2014 the conference has taken place every two years at the University’s Faculty of Electrical Engineering, Automatic Control and Informatics. The conference focused on the issues relating to new trends in modern brain–computer interfaces (BCI) and control engineering, including neurobiology–neurosurgery, cognitive science–bioethics, biophysics–biochemistry, modeling–neuroinformatics, BCI technology, biomedical engineering, control and robotics, computer engineering and neurorehabilitation–biofeedback.In addition to paper presentations, the scientific program also included a number of practical demonstrations covering, for example, the on-line control of mobile robot and unmanned aerial vehicle using the BCI technology.