摘要
For the convenience of people with disability and for normal people, a demand for intelligent interfaces is ever increasing and therefore related studies are actively being conducted. Recently a study is being conducted to develop an interface through face expression, movement of the body and eye movements, and further more active attempts to use electrical signals(brainwave, electrocardiogram, electromyogram) measured from the human body is also actively being progressed. In addition, the development and the usage of mobile devices and smart devices are promoting these research activities even more. The brainwave is measured by electrical activities between nerve cells in the cerebral cortex using scalp electrodes. The brainwave is mainly used for diagnosis and treatment of diseases such as epilepsy, encephalitis, brain tumors and brain damage. As a result, the brainwave measurement methods and analytical methods were developed. Interface using the brainwave will not go through language or body behavior which is the result of the information processed by the brain but will pass directly to the system providing a brain-computer interface (BCI). This is possible because a variety of the brainwave appears depending on the human’s physical and mental state. Using the brainwave with the intelligent brain-computer interface or combining it with mobile devices and smart devices, regardless of space constraints, the brainwave measurement should be possible.[4,7] In this study, in order to measure the brainwave without spatial constraint, 16 channel compact brainwave measurements system using a high-speed wireless communications were designed. It was designed with a 16 channel to classify the various brainwave patterns that appear and for estimating the location of the nerve cells that triggered the brainwave. And in order to transmit the brainwave data within the channel without loss, a high-speed wireless communication must be possible that can enable a high-speed wireless transmission more sufficient than the Bluetooth, therefore, 802.11 compliant Wi-Fi communication methods were used to transfer the data to the PC. In addition, by using an analog front-end IC having a single-chip configuration with real-time digital filters, the miniaturization of the system was implemented and in order to verify the system Eye-blocking was used to observe the changes in the EEG signal.
For the convenience of people with disability and for normal people, a demand for intelligent interfaces is ever increasing and therefore related studies are actively being conducted. Recently a study is being conducted to develop an interface through face expression, movement of the body and eye movements, and further more active attempts to use electrical signals(brainwave, electrocardiogram, electromyogram) measured from the human body is also actively being progressed. In addition, the development and the usage of mobile devices and smart devices are promoting these research activities even more. The brainwave is measured by electrical activities between nerve cells in the cerebral cortex using scalp electrodes. The brainwave is mainly used for diagnosis and treatment of diseases such as epilepsy, encephalitis, brain tumors and brain damage. As a result, the brainwave measurement methods and analytical methods were developed. Interface using the brainwave will not go through language or body behavior which is the result of the information processed by the brain but will pass directly to the system providing a brain-computer interface (BCI). This is possible because a variety of the brainwave appears depending on the human’s physical and mental state. Using the brainwave with the intelligent brain-computer interface or combining it with mobile devices and smart devices, regardless of space constraints, the brainwave measurement should be possible.[4,7] In this study, in order to measure the brainwave without spatial constraint, 16 channel compact brainwave measurements system using a high-speed wireless communications were designed. It was designed with a 16 channel to classify the various brainwave patterns that appear and for estimating the location of the nerve cells that triggered the brainwave. And in order to transmit the brainwave data within the channel without loss, a high-speed wireless communication must be possible that can enable a high-speed wireless transmission more sufficient than the Bluetooth, therefore, 802.11 compliant Wi-Fi communication methods were used to transfer the data to the PC. In addition, by using an analog front-end IC having a single-chip configuration with real-time digital filters, the miniaturization of the system was implemented and in order to verify the system Eye-blocking was used to observe the changes in the EEG signal.
