EEG-Based Personal Identification

Non

Investigation of Dynamic Transition of Learning Contents Based on Brain Waves

With the spread of the Internet, e-learning which is a way of learning using information technology has become popular. Although lecture videos in e-learning are designed so that many learners can understand, they do not take into consideration individual differences of learners. To address this problem, we designed a system that can grasp the concentration state of learners using electroencephalogram and dynamically provide contents according to the state. Moreover, we defined a metric using alpha waves in brain waves acquired from the occipital region as an index of changing learning materials used in the system. It enables providing suitable contents to each learner. In this research, we investigated the usefulness of the index and compared it with other brain waves such as theta waves and beta waves. As a result, it was confirmed that the proposed index was useful to extract learners who are relatively concentrating and not relatively concentrating. Moreover, it was suggested that alpha waves were more useful as the index for concentrating state than other waves

Towards Ambulatory Brain-Computer Interfaces: A Pilot Study with P300 Signals

Brain-Computer Interfaces (BCI) are communication systems that enable users to interact with computers using only brain activity. This activity is generally measured by ElectroEncephaloGraphy (EEG). A major limitation of BCI is the electrical sensitivity of EEG which causes severe deterioration of the signals when the user is moving. This constrains current EEG-based BCI to be used only by sitting and still subjects, hence limiting the use of BCI for applications such as video games. In this paper, we proposed a feasibility study to discover whether a BCI system, here based on the P300 brain signal, could be used with a moving subject. We recorded EEG signals from 5 users in 3 conditions: sitting, standing and walking. Analysis of the recorded signals suggested that despite the noise generated by the user’s motion, it was still possible to detect the P300 in the signals in each of the three conditions. This opens new perspective of applications using a wearable P300-based BCI as input device, e.g., for entertainment and video games

Improving the Efficiency and Antioxidant Activity of Essential Oil Extraction from Abies sachalinensis by Underwater Shockwave Pretreatment for the Construction of Low-Energy and Sustainable Essential Oil Extraction System

Essential oils (EOs) from Abies sachalinensis (Sakhalin fir), a conifer species found in Sakhalin Island and Hokkaido in Japan, effectively remove nitrogen dioxide and possess antifungal activity. EOs also exert a relaxing effect and enhance air quality. Underwater shock waves generate instantaneous high pressure that ruptures cell walls, enhancing the performance of steam distillation and oil extraction. In this study, we aimed to increase the yield and quality of A. sachalinensis extracts using shockwaves. Leaves and branches were subjected to shockwave pretreatment or left untreated before EO extraction by steam distillation. EO yield of untreated dried leaves was 2.4 g/kg of dry leaf weight (DW). Upon application of a 3.0 kV, 3.6 kJ shockwave, the yield increased with the number of shockwave cycles. After ten cycles, yield increased 13.6-fold. Pretreatment with shockwaves for 10 cycles resulted in approximately 6- and 13-fold reductions in total energy consumption relative to fresh and dried leaves, respectively. Antioxidant activity increased more than 30-fold in shockwave-pretreated leaves than in untreated dried leaves after 10 cycles. This novel process can significantly reduce the energy used for EO extraction in steam distillation, thereby contributing to the development of a sustainable, low-energy EO production system

Comprehensive Steroid Assay with Non-Targeted Analysis Using Liquid Chromatography Ion Mobility Mass Spectrometry

Aldosterone-producing adenomas (APAs) have different steroid profiles in serum, depending on the causative genetic mutation. Ion mobility is a separation technique for gas-phase ions based on their m/z values, shapes, and sizes. Human serum (100 µL) was purified by liquid–liquid extraction using tert-butyl methyl ether/ethyl acetate at 1/1 (v/v) and mixed with deuterium-labeled steroids as the internal standard. The separated supernatant was dried, re-dissolved in water containing 20% methanol, and injected into a liquid chromatography–ion mobility–mass spectrometer (LC/IM/MS). We established a highly sensitive assay system by separating 20 steroids based on their retention time, m/z value, and drift time. Twenty steroids were measured in the serum of patients with primary aldosteronism, essential hypertension, and healthy subjects and were clearly classified using principal component analysis. This method was also able to detect phosphatidylcholine and phosphatidylethanolamine, which were not targeted. LC/IM/MS has a high selectivity for known compounds and has the potential to provide information on unknown compounds. This analytical method has the potential to elucidate the pathogenesis of APA and identify unknown steroids that could serve as biomarkers for APA with different genetic mutations