Kyushu University Academic Staff Educational and Research Activities Database
List of Presentations
Keiji Iramina Last modified date:2024.04.26

Professor / Intelligent Science / Department of Informatics / Faculty of Information Science and Electrical Engineering


Presentations
1. @Keiji Iramina, Working memory study using EEG and NIRS for early detection and intervention ADHD, 2023 Coference Korean Society of EEG and Neurophysiology, 2023.12.
2. Yueling Zhang, Keiji Iramina , Linear Relationship between Corticomusclar Coherence and Upper Limb Voluntary Contraction, BMEiCON2023, 2023.10, In this study, we investigated ‘pain recall' that results from showing a painful image and evoking pain without actually giving any pain, that is said to be similar to the brain activity that actually causes pain. The experiment involved 12 students showing three short videos in which a child, a female, or a male was being injected. We measured the degree of emotional changes by watching the painful scene in three ways: emotion estimation by facial expression, GSR (Galvanic Skin Response) and Eye tracking. The results showed that subjects felt the same fear and tension as when feeling pain. On the other hand, subjects felt less painful emotions when they looked at the scene that a man with solid arms was injected. The degree of emotion in pain recall varied depending on who received the injection in the short videos. These results suggest that pain may be reduced by showing some body image as visual information. It is possible to alleviate actual pain by applying how to reduce ‘pain recall'. .
3. Nina Itagaki, Yutaro Nakada, Keiji Iramina , The effect of visual cognition on the fear caused by pain recall , BMEiCON2022, 2022.07, In this study, we investigated ‘pain recall' that results from showing a painful image and evoking pain without actually giving any pain, that is said to be similar to the brain activity that actually causes pain. The experiment involved 12 students showing three short videos in which a child, a female, or a male was being injected. We measured the degree of emotional changes by watching the painful scene in three ways: emotion estimation by facial expression, GSR (Galvanic Skin Response) and Eye tracking. The results showed that subjects felt the same fear and tension as when feeling pain. On the other hand, subjects felt less painful emotions when they looked at the scene that a man with solid arms was injected. The degree of emotion in pain recall varied depending on who received the injection in the short videos. These results suggest that pain may be reduced by showing some body image as visual information. It is possible to alleviate actual pain by applying how to reduce ‘pain recall'. .
4. Misato Oka, Junna Muta, Kiko Sato, Eiji Ikuta,Keiji Iramina, Effect of Working Memory Training on Learning Ability of High School Students, 13th Biomedical Engineering International Conference (BMEiCON), 2021.11.
5. Fumiya Sanuki, Haruki Nishimura, Shodai Suehiro, Keiji Iramina, Comparison of brain activity in success and failure in single and multitask game, 13th Biomedical Engineering International Conference (BMEiCON), 2021.11.
6. Keiji Iramina, Measurement of prefrontal cortex activity to attention conflicts in working memory by NIRS, The 10th International Conference on Science and Engineering, 2019.12.
7. Nyi Nyi Tun, Keiji Iramina, RELATIONSHIP BETWEEN EMG ANDERD/ERS DURING MOTOR IMAGERY BASED ON THE MUSCLE CONTRACTION
TYPES, 2019 Joint International Conference on Science, Technology and Innovation, Mandalay by IEEE, 2019.09.
8. Tanaka Shu, Hayami Takehito, Wongsawat Yodchanan, Tiawongsuwan Lattika, Yamada Kenji, Ikuta Koji, Iramina Keiji, An Analysis of Photic Driving EEG Evoked with Sets of Color Flashes from the Glasses Having the Luminous Function, LE Symposium 2019, 2019.08.
9. Hiroto Takeuchi, Keiji Iramina, The effect of the combined working memory and fm theta neurofeedback training for attention and working memory, LE Symposium 2019, 2019.08.
10. Van Le Thi Cam, Ayumi Tahara, Nonthaporn Nakphu, Keiji Iramina, The effect of background music on attention at different difficulty levels of video game, LE Symposium 2019, 2019.08.
11. Shota Hatano, Sho Ageno, Lattika Tiawongsuwan, Sansit Ngamrassameewong, YodchananWongsawat, Keiji Iramina, Case Study: Autism Spectrum Disorder's Unique Brain Activity During Mental Arithmetic, LE Symposium 2019, 2019.08.
12. Sho Ageno, Shota Hatano, Keiji Iramina, Investigation of EEG-DMN using Phase Locking Value, LE Symposium 2019, 2019.08.
13. Zhaoxuan Li, De Bi, Wanqin Ma, Keiji Iramina, Activation in Somatosensory Cortex during Object Recognition Procedure, LE Symposium 2019, 2019.08.
14. Ruimin Wang, Keiji Iramina, Contribution of prefrontal cortex to attention conflicts in dual memory tasks, LE Symposium 2019, 2019.08.
15. Nyi Nyi Tun, Keiji Iramina, Investigation of the relation between muscle activity and motor imagery based on the muscle contraction types, LE Symposium 2019, 2019.08.
16. Ayumi Tahara, Nonthaporn Nakphu, Van Le Thi Cam, Thitikorn Kaewlee, YodchananWongsawat, Keiji Iramina, EEG Activity during Playing Game Design for Neurofeedback, LE Symposium 2019, 2019.08.
17. Fumiya Sanuki, Khanittha Kiatbamrungpunt, Keiji Iramina, Comparing ERD/ERS pattern of motor imagery in VR and No-VR condition, LE Symposium 2019, 2019.08.
18. Toshihiro Tamura, Ruimin Wang, Keiji Iramina, Effects of auditory white noise on visual working memory, LE Symposium 2019, 2019.08.
19. Ruimin Wang, Ge Shegn, Zommara Noha Mohsen, Zheng WenWei, Keiji Iramina, Auditory White Noise Affects Left/Right Visual Working Memory in an Opposite Pattern, Engineering in Medicine and Biology Society (EMBC), 2019 41th Annual International Conference of the IEEE, 2019.07.
20. Tahara Ayumi, Nakphu, Nonthaporn, Le Thi Cam, Van, Kaewlee Thitikorn, Wongsawat Yodchanan, Keiji Iramina, Investigation of EEG Activity in the Different Events during Playing Game, Engineering in Medicine and Biology Society (EMBC), 2019 41th Annual International Conference of the IEEE, 2019.07.
21. Fadilla Zennifa Keiji Iramina, Exploring Hjorth parameter in EEG-ECG-NIRS Features toward Engagement States, 2019年 日本生体医工学会九州支部学術講演会 , 2019.03.
22. Zebin Xu #Zhaoxuan Li Keiji Iramina, The BCI Speller based on SSVEP using Virtual Reality, 電子情報通信学会 MEとバイオサイバネティックス研究会, 2019.01.
23. Chen Zhuoheng Keiji Iramina, An Asynchronous SSVEP-based Brain Computer Interface Japanese Speller -- Research Report --, 電子情報通信学会 MEとバイオサイバネティックス研究会, 2019.01.
24. Wenwei Zheng Ruimin Wang Noha Zommara Keiji Iramina, Temporal/Spatial congruency aspect of the auditory affection on visual working memory, 電子情報通信学会 MEとバイオサイバネティックス研究会, 2019.01.
25. Keiji Iramina, Evaluation of Soft Neurological Signs by Measurement of Pronation and Supination, The Nineth International Conference on Science and Engineering, 2018.12.
26. R. M. Wanga, K. Iraminaa, The linear relationship of prefrontal cortex activation with working memory capacity: Evaluating individual difference by pure tone sequences, fNIRS2018, 2018.10.
27. Nyi Nyi Tun, Keiji Iramina, Extracting EMG Features of Fingers and Hand Movements, The Nineth International Conference on Science and Engineering, 2018.06.
28. Le Thi Cam Van, Le Thanh Nhan, Nguyen Ngoc Hai, Le Cao Dang, Keiji Iramina, Controlling the wheelchair by eye movements using EEG, The 7th International Conference in Vietnam on the Development of Biomedical Engineering, 2018.06.
29. fadilla Zeniffa, Junko Ide , Yukio Noguchi, Keiji Iramina, Integrated Monitoring System by Wireless EEG, ECG, NIRS in Neurodevelopmental Disorder Children during Theraphy, The Eighth International Conference on Science and Engineering, 2017.12.
30. Keiji Iramina, Measurement ofControl of Human Brain Dynamics, The Eighth International Conference on Science and Engineering, 2017.12.
31. Gaopeng Sun, Hui Liu, Yanhua Shi, Yue Leng, Pan Lin, Ruimin Wang, Yuankui Yang, Junfeng Gao, Haixian Wang, Keiji Iramina, Sheng Ge, One class support vector machine based filter for improving the classification accuracy of SSVEP BCI, Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017.10, Canonical correlation analysis (CCA) has been proved to be effective in the detection of steady state visual evoked potential (SSVEP) signals. However, the CCA method only chooses the frequency in the reference mode that corresponds to the maximum correlation value as the target. This may make the CCA output less robust. In this study, we propose a one-class support vector machine based filter to filter the sequences of correlation values in the process of the detection of SSVEP signals. The results demonstrate that the classification accuracy improved over different time windows for all subjects and the improvement achieved approximately 10% for some subjects. Moreover, the ratio of instructions that were filtered incorrectly was relative low (less than 5%) if the SSVEP signals were generated effectively..
32. Hui Liu; Wengming Zheng; Gaopeng Sun; Yanhua Shi; Yue Leng; Pan Lin; Ruimin Wang; Yuankui Yang; Jun-feng Gao; Haixian Wang; Keiji Iramina; Sheng Ge, Action understanding based on a combination of one-versus-rest and one-versus-one multi-classification methods, Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017.10, When people observe the actions of others, they naturally try to understand the underlying intentions. This behavior is called action understanding, and it has an important influence on mental development, language comprehension, and socialization. In this study, we used functional near-infrared spectroscopy (fNIRS) to obtain brain signals related to action understanding and then classified different intentions. Aiming to overcome the drawbacks of traditional multiclass classification methods of one-versus-rest (OVR) and one-versus-one (OVO), in this paper, we propose a new effective method to solve multiclass classification that is a combination of OVR and OVO. Compared with OVO, this new method effectively improved the accuracy of four-class classification from 25% to 48%..
33. Chayapol Chaiyanan; Keiji Iramina; Thanate Angsuwatanakul; Boonserm Kaewkamnerdpong, Response time analysis on implicit learning induced by cognitive tasks toward developing ADHD treatment, Biomedical Engineering International Conference (BMEiCON), 2017.09, Attention Deficit Hyperactivity Disorder is a neurological disorder that affects many children in the world. Many scientists have speculated that behavior therapy is an essential part of treatment for people with ADHD. One of the promising behavioral therapy is neurofeedback therapy. Using neurofeedback, therapist can learn how to modulate patients' brain activity by adjusting the training regimen. Identifying when a patient achieve implicit learning event can potentially help in designing the neurofeedback treatment to help people with ADHD. According to past research, it was speculated that implicit learning and children with ADHD could have an atypical relationship. The aim of this paper to analyze response times of healthy people while they perform cognitive tasks to differentiate between people who has gained implicit knowledge and those who did not. The data showed that there is a clear distinction between people who had gained implicit knowledge and those that did not..
34. Ruimin Wang, Risako Kamezawa, Aiko Watanabe, Keiji Iramina, EEG alpha power change during working memory encoding in adults with different memory performance levels, Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE, 2017.07, Working memory (WM) capacity affects our daily life in many ways, and its decrease often associates with neural disorders (e.g. Alzheimer's disease). Several studies have confirmed that alpha rhythms play an active role in memory mechanism. In the present study, we designed a digit verbal span experiment to find out that how the alpha power change during working memory encoding, and the relationship between alpha power and individual WM performance. Consistent with previous studies, our results confirm that alpha power is positively related to WM performance. Participants who had higher alpha power during WM encoding achieved better memory performance. We can conclude that the reason is alpha rhythms reflect inhibition of task-irrelevant information. Howbeit, a linear relationship between WM load and alpha power amplitude during memory encoding cannot be deduced in our experiment..
35. Tustanah Phukhachee; Suthathip Maneewongvatana; Boonserm Kaewkamnerdpong; Thanate Angsuwatanakul; Keiji Iramina, Measuring brain activation by using baseline-normalized event-related spectral perturbation in working memory task, Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE, 2017.07, Understanding the cognitive function of human brain is an important step in providing scientific evidence which could help us improve the condition of memory disorders, slow down its progress or at least help the patients retain some important matters. In this study, we aimed to provide additional scientific evidence with more insight on how the brain functions at a good/bad cognitive state than the usual statistical analysis. We introduced the brain activation measurement using baseline-normalized ERSP to determine the activation of EEG data from stimuli. These active points over a period of time could reflect brain synchronization due to stimuli. We also demonstrated the use of proposed measure on attention working memory data. The results indicate the potential of using the proposed measurement in categorizing the brain cognitive state and identifying some important factors to provide additional evidence to the field in the future..
36. Jongseung Lee; Nobutaka Mukae; Jumpei Arata; Hiroyuki Iwata; Keiji Iramina; Koji Iihara; Makoto Hashizume, A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients, 2017 International Conference on Rehabilitation Robotics (ICORR), 2017.07, There is a demand for a new neurorehabilitation modality with a brain-computer interface for stroke patients with insufficient or no remaining hand motor function. We previously developed a robotic hand rehabilitation system triggered by multichannel near-infrared spectroscopy (NIRS) to address this demand. In a preliminary prototype system, a robotic hand orthosis, providing one degree-of-freedom motion for a hand's closing and opening, is triggered by a wireless command from a NIRS system, capturing a subject's motor cortex activation. To examine the feasibility of the prototype, we conducted a preliminary test involving six neurologically intact participants. The test comprised a series of evaluations for two aspects of neurorehabilitation training in a real-time manner: classification accuracy and execution time. The effects of classification-related factors, namely the algorithm, signal type, and number of NIRS channels, were investigated. In the comparison of algorithms, linear discrimination analysis performed better than the support vector machine in terms of both accuracy and training time. The oxyhemoglobin versus deoxyhemoglobin comparison revealed that the two concentrations almost equally contribute to the hand motion estimation. The relationship between the number of NIRS channels and accuracy indicated that a certain number of channels are needed and suggested a need for a method of selecting informative channels. The computation time of 5.84 ms was acceptable for our purpose. Overall, the preliminary prototype showed sufficient feasibility for further development and clinical testing with stroke patients..
37. Keiji Iramina, Introduction to BME in SLS, Research in Neuroimaging, International Collaborative Workshop on Biomedical Engineering: - Focus on Interdisciplinary Education and Research -, 2017.01.
38. Thanate Angsuwatanakul, Keiji Iramina, Analysis of Brain Complexity with Simultaneous EEG-NIRS in Working Memory Study, International Collaborative Workshop on Biomedical Engineering: - Focus on Interdisciplinary Education and Research -, 2017.01.
39. Yoshiyuki Shiotsuka, Keiji Iramina, Simultaneously Measurement of Eye Tracking and EEG In Posner’s Task, International Collaborative Workshop on Biomedical Engineering: - Focus on Interdisciplinary Education and Research -, 2017.01.
40. Aya Sato, Keiji Iramina, Effects of Peripheral Magnetic Stimulation on motor cortical excitability, International Collaborative Workshop on Biomedical Engineering: - Focus on Interdisciplinary Education and Research -, 2017.01.
41. Keiji Iramina, Measurement and Control of Human Brain Dynamics, ICSE2016, 2016.12, This study focuses on measuring and controlling of human brain dynamics using noninvasive techniques. I will give two topics in this study. One is a transcranial magnetic stimulation (TMS) which is possible to control of neuronal excitability. We applied TMS to cognitive studies for visual perceptions. The other one is a non-restraint cognitive monitoring system and its’ application to a child with mental deficiency. The objective our system is toward gaining information about the actual user state, including intentions, situational interpretations and emotions..
42. Aya Sato, Xiangqun Liu, Tesuya Torii, Masakuni Iwahashi, Keiji Iramina, Modulation of Motor Cortex Excitability by Peripheral Magnetic Stimulation of Different Stimulus Sites and Frequencies, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Soceity, 2016.08, Peripheral stimulation is known to influence the state of cortical excitability. The purpose of this study is to investigate whether peripheral magnetic stimulation has similar effects on cortical excitability to transcranial magnetic stimulation (TMS). A magnetic stimulator with a flat figure-of-eight coil was used for both TMS, and peripheral magnetic stimulation applied to the bilateral forearms. TMS was performed on the left primary motor cortex to evaluate influence of the peripheral magnetic stimulation, and motor evoked potential (MEP) was measured from the right first dorsal interosseous. Peripheral magnetic stimulation was performed at a stimulus frequency of 1 Hz or 10 Hz, to the stimulus sites on the right and left supination of the forearm. The effects of peripheral magnetic stimulation were evaluated by comparing the mean MEP amplitude elicited by TMS before and after peripheral magnetic stimulation. We found that cortical excitability varied according to the stimulation site and frequency of the peripheral magnetic stimulation. The inhibition of cortical excitability was observed following 1 Hz peripheral magnetic stimulation over the right forearm (p
43. Ruimin Wang, Keiji Iramina, Sheng Ge, An Improved Multiple LASSO Model for Steady-State Visual Evoked Potential Detection, The 6th International Conference on the Development of Biomedical Engineering, 2016.06, Improving the classification accuracy in brain–computer interface (BCI) with a short data length is important to increase the BCI system’s information transfer rate. Least absolute shrinkage and selection operator (LASSO) has been examined to be an effective way to detect the steady-state visual evoked potential (SSVEP) signals with a short time window. In this paper, an improved multiple LASSO model for SSVEP detection is proposed, which can process multichannel electroencephalogram (EEG) signals without electrode selection. EEG data from twelve healthy volunteers were used to test the improvedmultiple LASSO model. Compared with the traditional LASSO model, the improved multiple LASSO model gives a significantly better performance with multichannel EEG data..
44. Takehito Hayami, Keiji Iramina, Xian Chen, Computer Simulation of Nerve Conduction Study of a Sural Nerve to Evaluate Human Peripheral Nervous System, The 6th International Conference on the Development of Biomedical Engineering, 2016.06, Nerve conduction study is a test to examine the function of electric signal transmission at the trunk of a peripheral nerve, which is an effective method for the diagnosis of diabetes to quantify the peripheral numbness and to evaluate the stage of this complication. In a routine test, the feature to measure in the electric potential waveform observed in this test is limited to the velocity and the amplitude of the peaks. To make the measurement more precise, the production process of the electric potential waveform should be observed carefully. In this study, nerve conduction study of a sural nerve, which is the most popular for the patients with diabetes, was simulated in a computer using general cable equation and neuroanatomical data. As a result, the approximate electric
potential waveform was reproduced, whereas the conduction velocity of the peaks was not completely conformed to the physiological data..
45. Kurniawan Eka Permana, Tsuyoshi Okamoto, Keiji Iramina, Single Channel Electroencephalogram Measurement with Multi Scale Entropy Analysis for Evaluating Day Time Sleep, The 6th International Conference on the Development of Biomedical Engineering, 2016.06, Nerve conduction study is a test to examine the function of electric signal transmission at the trunk of a peripheral nerve, which is an effective method for the diagnosis of diabetes to quantify the peripheral numbness and to evaluate the stage of this complication. In a routine test, the feature to measure in the electric potential waveform observed in this test is limited to the velocity and the amplitude of the peaks. To make the measurement more precise, the production process of the electric potential waveform should be observed carefully. In this study, nerve conduction study of a sural nerve, which is the most popular for the patients with diabetes, was simulated in a computer using general cable equation and neuroanatomical data. As a result, the approximate electric
potential waveform was reproduced, whereas the conduction velocity of the peaks was not completely conformed to the physiological data..
46. Aya Sato, Xiangqum Liu, Masakuni Iwahashi, Keiji Iramina, Alteration of the Motor Cortex Excitability by Modulation of the Stimulus Parameter of Peripheral Stimulation, The 6th International Conference on the Development of Biomedical Engineering, 2016.06, Transcranial magnetic stimulation (TMS) is known to elicit a conditioning effect on cortical excitability. The purpose of this study was to investigate changes in cortical excitability induced by peripheral stimulation with differing frequency and stimulation site. A magnetic stimulator with a flat figure-eight coil was used for TMS and was performed on the left primary motor cortex. The electrical stimulation and magnetic stimulation were used in peripheral stimulation and the stimulus sites were the right and left supination of the forearm. Peripheral stimulation was performed at a stimulus frequency of 1 Hz or 10 Hz. Alterations of cortical excitability induced by peripheral stimulation were evaluated by comparing the mean of the motor evoked potential amplitude elicited by TMS each before and after peripheral stimulation. We found that cortical excitability varied according to the stimulation site and frequency in both the electrical and magnetic stimulation over the forearm. The inhibition of cortical excitability
was observed in both 1 Hz electrical and magnetic stimulation over the right forearm. In contrast, the facilitation of cortical excitability was observed at 1 Hz electrical and magnetic stimulation over the left forearm, and it was confirmed for both the right and left forearms at 10 Hz electrical and magnetic stimulation. Moreover, regarding the alteration of cortical excitability induced by peripheral stimulation, it was confirmed that magnetic stimulation has more the significant difference than electrical stimulation. We suggest that peripheral stimulation by electrical and magnetic stimulation have a similar effect to TMS, and can induce both facilitation and inhibition of cortical excitability. Moreover, in the case of peripheral stimulation of the same stimulus frequency, we expect that the magnetic stimulation has more the significant effect than electrical stimulation to cortical excitability..
47. Keiji Iramina, Simultaneous Measurement of NIRS and EEG, 8th Chula Neurology Forum 2016, 2016.03, Near infrared Spectroscopy(NIRS) is a measurement of hemodynamic activity of the brain. On the other hand, EEG measures neuronal activity of the brain. Although both techniques can reveal the brain function, each measurement has several different charact.
48. MIki Kaneko, Keiji Iramina, Quantitative Evaluation System of Pronation and Supination for Children with
Attention Deficit Hyperactivity Disorder, Winter School at Systems Life Sciences Kyushu University, 2016.01.
49. Keiji Iramina, Introduction to BME in SLS, Research in Neuroimaging, Winter School at Systems Life Sciences Kyushu University, 2016.01.
50. Thanate Angsuwatanakul, Keiji Iramina, Analysis of Brain Complexity with Simultaneous EEG-NIRS in Working Memory Study, Winter School at Systems Life Sciences Kyushu University, 2016.01.
51. Fadilla Zenifa, Keiji Iramina, Investigate the Neurophysiology and hemodynamic changes during training in Mental retardation child Using EEG-ECG-NIRS, Winter School at Systems Life Sciences Kyushu University, 2016.01.
52. Thanate Angsuwatanakul, Keiji Iramina, Boonserm Kaewkamnerdpong, Brain Complexity Analysis of Functional Near Infrared Spectroscopy for Working Memory Study
, 8th Biomedical Engineering International Conference, 2015.11, This study proposed an alternative approach for analyzing visual working memory based on brain complexity to identify brain state condition for memorizing new scenes. Multi-scale entropy (MSE) was used for analyzing the complexity of Near Infrared Spectroscopy (NIRS) data which measured the hemodynamic response of brain during a cognitive experiment. The results revealed the distinctive entropy between remembered and forgotten cases in prefrontal area at FC3 position. The entropy of remembered case is higher than forgotten case; this could indicate that the brain requires more activity and then more hemodynamic responses for good memorizing. Hence, the results indicated the potential of using the complexity of NIRS for characterizing the brain state for working memory. .
53. Masaki Ono, Hiroki Furusyo, Keiji Iramina, Analysis of the complexity of EEG during the short-term memory task
, 8th Biomedical Engineering International Conference, 2015.11, By using fractal dimension and sample entropy, we investigated the complexity electroencephalogram (EEG) during an activity that uses working memory. We conduct a short-term memory test and a calculation task and analyzed 1.0s EEG data from 4 phases (resting, encoding, retrieval and calculation phase). As a result, fractal dimension analysis can reflect the activity ofthe working memory better than sample entropy analysis. Moreover, in order to investigate the relationship between the fractal dimension value and the power of theta band (4-8 Hz) in the frontal region, we conducted a correlation coefficient analysis. The result showed that increase of the power of theta band and decrease of fractal dimension value has relatively high correlation. In conclusion, the activity of working memory in frortal
part may be able to be captured by fractal dimension analysis..
54. Kazuki Onikura, Keiji Iramina, Evaluation of a head movement artifact removal method for EEG considering real-time prosessing
, 8th Biomedical Engineering International Conference, 2015.11, The present study proposes the method of removing head movement artifact for considering real-time processing and improving reliability of EEG under unconstrained measurement. In the proposed method, independent component analysis and high-pass filtering were usefi with a hybrid accelerometer, which was used for detecting components containing head movement artifact. To evaluate the proposed method, we measured EEG which included the artifact and P300 components. As a result, although EEG amplitude decreased, original P300 waveform appeared clearly. This result indicates that the proposed method is effective for removing head movement artifact while keeping EEG information..
55. Yuya Onitsuka, Yoshiyuki Shiotsuka, Keiji Iramina, The difference in the kinds of stimulations in CIT based on ERP
, 8th Biomedical Engineering International Conference, 2015.11, The topic of our research is the detection of concealed information based on ERP (Event Related Potential). As a method to detect concealed information there is CIT (Concealed Information Test). CIT is used to detect intentionally concealed information, for example crime-related information, with subject’s physiological response to presented stimuli. We used visually CIT based on P300 in the experiment. There are three kinds of stimuli in CIT. One is ‘Probe’, which is related to concealed information. The other is ‘Irrelevant’, which is not related with it but consists of same category as Probe (ex; place, time and so on). And the other is ‘Target’, which is for calling subject’s attention to the experiment. In CIT, the subject’s reaction to those presented stimuli are measured and compared with each other
categories. If the reaction to Probe are different with one to Irrelevant the subject is considered as he knows Probe..
56. Keiji Iramina, Evaluation of soft neurological signs in ADHD children by measurement of pronation and supination, IEEE TENCON2015, 2015.11.
57. Abdullah Basuki Rahmat , Keiji Iramina, Classification of Multiclass EEG Signal Related to Mental Task Using Higuchi Fractal Dimension and 10-Statistic Parameters - Support Vector Machine, IEEE TENCON2015, 2015.11.
58. Miki Kaneko, Keiji Iramina, Volatility of Pronation and Supination in Children with ADHD , 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Soceity, 2015.08, Pronation and supination of forearms is one of diagnostic methods for attention deficit hyperactivity disorder (ADHD). Our aim is to establish a quantitative evaluation system for this movement using acceleration and angular velocity sensors. In this study, we compared pronation and supination of forearms between typically developing children and children with ADHD..
59. Fadilla Zennifa, Junko Ide, Yukihiro Noguchi, Keiji Iramina, Monitoring of Cognitive State on Mental Retardation Child using EEG, ECG and NIRS in Four Years Study, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Soceity, 2015.08.
60. Kazuki Onikura, Keiji Iramina, Inspection of the motion artifact removal method for EEG using ICA and filtering, 7th Biomedical Engineering International Conference, 2014.11, Artifacts which contaminate EEG signals makes it difficult to analyze EEG. The aim of this study is the removal of artifacts, especially those caused by motion, to measure EEG in any situation. Using the proposed removal method based on ICA and filtering, the amplitude of cleaned EEG was 25 μV lower than raw EEG and the ratio (alpha power / low power) of cleaned EEG was twice higher than raw EEG..
61. Takaaki Mizuba, Chihiro Karube, Keiji Iramina, The Cerebral Blood Responses to Subject’s Own Name:
A NIRS Study, 7th Biomedical Engineering International Conference, 2014.11, One’s own name plays important roles as biological markers. In the present study, we used the near-infrared spectroscopy (NIRS) and focused on cerebral blood flow responses, when hearing one’s own name. Our result indicated that prefrontal cortex (PFC) was activated by one’s own name. This finding suggested that the high cognitive functions were induced by one’s own name..
62. Takaaki Mizuba, Kaori Tamura, Keiji Iramina, Subject’s Own Name and Unknown Names: An ERP Study, 7th Biomedical Engineering International Conference, 2014.11, ERP responses to hearing one’s own name have been investigated. In this study, we compared ERP responses between SON (subject’s own name) and UN (unknown names) while taking the UN’s repetition effect into account. Our result showed that SON elicited the late positive wave at parietal sites. This finding indicated that SON was recognized as high self-related stimulus..
63. Fadilla Zennifa, Hikaru Kinoshita, Junko Ide, Yukihiro Noguchi, Keiji Iramina, The Investigation of Heart Rate Variability during Training in Children with Mental Retardation by ECG, 7th Biomedical Engineering International Conference, 2014.11, Individual with Mental retardation usually exhibit cardiovascular abnormalities. This study investigated HRV value in mental retardation children during training program to know the difference value of HRV between resting and non resting activity. In order to evaluate the measurement results based on HRVs, four major measurements were calculated in this study. Result showed the value between of SDNN and RMSSD in all activities are linear. In conclusion the HRV value in resting state and non-resting state is not different..
64. Hikaru Kinoshita, Fadilla Zennifa, Junko Ide, Yukihiro Noguchi, Keiji Iramina, The Comparison of brain activity from Developmental Disorder Children by NIRS - EEG with Teacher Score during Training, 7th Biomedical Engineering International Conference, 2014.11, This study used NIRS and EEG to measure the brain activity of developmental disorder children. This study investigated the change concentration of oxygen hemoglo bin in forehead by using NIRS. In the same time, this study evaluated the value of frequency theta and beta wave by using EEG. The aim of this study is comparing the analysis result of EEG, NIRS score with teacher score in training activity of developmental disorder. .
65. Akinari Miwa, Keiji Iramina, Analysis of Bimanual Coordination for The Diagnosis Evaluation of Parkinson's Disease using Image Processing, 7th Biomedical Engineering International Conference, 2014.11, The diagnosis evaluation of the Parkinson's disease (PD) isn't quantitative because the movement of the patient is analyzed by the visual decision of doctor. The aim of this study is to establish evaluation methods quantitative and simple for diagnosing PD's symptoms and the therapeutic effect using the movie of a video camera. In this study, the bimanual coordination experiment was carried out with healthy subjects, and the result was analyzed for examining the evaluation method of the movement.
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66. Binbin Chen, Akira Yamamoto, Keiji Iramina, Preliminary experiment on healthy for treatment of Parkinson’s disease patients with rTMS, 7th Biomedical Engineering International Conference, 2014.11, Cortical excitability in PD patients is expressed like shortened cortical silent period (CSP) and an abnormal motor evoked potential (MEP) size.This study focused on cortical excitability modulation by rTMS in healthy.
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67. Hanung Nugroho, Christianus Hotama, Keiji Iramina, Comparison of Time Frequency Analysis during Word-task and Color-task in the Stroop Task, 7th Biomedical Engineering International Conference, 2014.11, We use EEG during stroop task to see how the brain works during the concentration test. By using time frequency analysis, we can analyze the frequency band that will have the higher power spectral density and the difference of active potential between left-frontal lobe (Fp1, F3) and right-frontal lobe (Fp2,F4) during word-task and color-task of stroop task. .
68. Kazuya Sannomiya, Keiji Iramina, Evaluation of Current Density Distribution of tDCS in the Brain by computer simulation -Differences in Electrodes Position, 7th Biomedical Engineering International Conference, 2014.11, — Transcranial direct current stimulation (tDCS) is noninvasive brain stimulation method that modulate cortical excitability by direct current. The use of tDCS is increasing in a variety of clinical fields as treatment for neuropsychiatric disease and neurological disorders. But it isn’t obvious how brain is affected by tDCS. In this study, we investigated the difference of current density distribution in brain by computational model. The aim is to estimate the difference of current density distribution in brain for position of tDCS electrodes. As a result, it turned out that the distance of two electrodes is one of important parameter.
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69. Keita Higashi, Keiji Iramina, Evaluation of Hand Motor Function in Mild Cognitive Impairment Patients by Pronation and Supination of Forearms
, 7th Biomedical Engineering International Conference, 2014.11, This paper describes the difference of hand motor function between healthy people and people with mild cognitive impairment (MCI). The aim of this study is to investigate characteristics of complex hand motor function in MCI patients. In this study, pronation and supination of forearms of 45 elderly people were examined. We obtained the difference between healthy controls and MCI patients.
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70. Yuki Noguchi, Miki Kaneko, Keita Higashi, Yasushi Miyagi, R Murayama, Keiji Iramina, Yoshinori Katayama, Evaluation for Treatment of Deep Brain Stimulation by Pronation and Supination of Forearms using Wireless Sensors
, 7th Biomedical Engineering International Conference, 2014.11, Deep brain stimulation (DBS) is one of treatment for Parkinson’s Disease (PD). The diagnosis of Parkinson’s Disease is difficult because of its complexity.
Therefore, we have established an evaluation for the effect of treatment in DBS. We measure pronation and supination of forearms, which is used for diagnosis of PD, and analyze the motion of subjects by obtained acceleration and angular velocity. We use two indices for analysis. These indices by obtained results are useful for evaluation of treatment of DBS.
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71. Keiji Iramina, Evaluation of pronation and supination: comparison between typically developing children and children with AD/CD, BioApps 2014, 2014.11.
72. Fadilla Zennifa, Fitrilina, Husnil Kamil, Keiji Iramina, Prototype early warning system for heart disease detection using Android application, 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014.08, Heart Disease affects approximately 70 million people worldwide where most people do not even know the symptoms. This research examines the prototype of early warning system for heart disease by android application. It aims to facilitate users to early detect heart disease which can be used independently. To build the application in android phone, variable centered intelligence rule system (VCIRS) as decision makers and pulse sensor - Arduino as heart rate detector were applied in this study. Moreover, in Arduino, the heart rate will become an input for symptoms in Android Application. The output of this system is the conclusion statement of users diagnosed with either coronary heart disease, hypertension heart disease, rheumatic heart disease or do not get any kind of heart disease. The result of diagnosis followed by analysis of the value of usage variable rate (VUR) rule usage rate (RUR) and node usage rate (NUR) that shows the value of the rule that will increase when the symptoms frequently appear. This application was compared with the medical analysis from 35 cases of heart disease and it showed concordance between diagnosis from android application and expert diagnosis of the doctors..
73. Chihiro Karube, Kaori Tamura, Keiji Iramina, Response to Subject’s Own Names measuring Near-Infrared Spectroscopy, 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014.08, Brain response to own name is a strong distracter. In this study we analyzed the brain response to subject’s own name by Near-Infrared Spectroscopy (NIRS). We found that Oxy-Hb increased after hearing subject’s own name specifically. It was suggested that this Oxy-Hb change was a result of recognition function of own name..
74. Miki Kaneko, Yushiro Yamashita, Keiji Iramina, Pronation and Supination of Children with ADHD, 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Soceity, 2014.08, Pronation and supination of forearms is one of diagnostic methods for attention deficit hyperactivity disorder (ADHD). Our aim is to establish a quantitative evaluation system for this movement using acceleration and angular velocity sensors. In this study, we compared pronation and supination of forearms between typically developing children and children with ADHD..
75. Miki Kaneko, Hiroshi Okui, Keita Higashi, Yuki Noguchi, Yoshinori Katayama, Takashi Ohya, Yushiro Yamashita, Keiji Iramina, The Comparison of Pronation and Supination between Typically Developing Children and Children with ADHD, The International MultiConference of Engineers and Computer Scientists 2014, 2014.03.
76. Fadilla Zennifer, Fitrilina, Husnil Kamil, 伊良皆 啓治, Independent Expert System for Early Detection of Heart Disease Using Varable Centered Intelligent Rule System, Pulse Sensor - Arduino ADK and Android Phone, 平成26年度日本生体医工学会九州支部学術講演会, 2014.03.
77. Keiji Iramina, Hikaru Kinoshita, Kaori Tamura, Chiro Karube, Junko Ide, Yukio Noguchi, Measurement of neuronal activity of the mentally-retarded child without restraint using wireless EEG, International Conference on Basic & Clinical Multimodal Imaging, 2013.09.
78. Kaori Tamura, Chiro Karube, Takaaki Mizuba, Keiji Iramina, EEG response to subjects' own name in patients with severe motor and intellectual disabilities, International Conference on Basic & Clinical Multimodal Imaging, 2013.09.
79. Kaori Tamura, Chiro Karube, Takaaki Mizuba, Mayumi Matsufuji, Sachio Takashima, Keiji Iramina, Measurement of brain activity responded by subjects'own name using EEG, The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), 2013.07.
80. Kaori Tamura, Chiro Karube, Takaaki Mizuba, Mayumi Matsufuji, Sachio Takashima, Keiji Iramina, Brain responses of Severe motor and intellectual disabilities (SMID), The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), 2013.07.
81. Miki Kaneko, Hiroshi Okui, Keita Higashi, Yuki Noguchi, Yoshinori Katayama, Keiji Iramina, The Comparison of Neuromotor Function between Dominant Hand and Non-Dominant Hand in Pronation and Supination of Forearms, The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), 2013.07.
82. Aya Sato, Tetsuya Torii, YU子Nakahara, Masakuni Iwahashi, Keiji Iramina, The impact of rTMS over the dorsolateral prefrontal cortex on cognitive processing, The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), 2013.07.
83. Kazuhisa Nojima, Yoshinori Katayama, Keiji Iramina, Measurement of brain activity responded by subjects'own name using EEG, The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), 2013.07.
84. Frequency-Dependent Effect of Slow-Frequency Repetitive Transcranial Magnetic Stimulation to Supramarginal Gyrus on Event-Related Potentials.
85. rTMS and tDCS to the motor cortex modulate the power of mu wave.
86. Pemoval of artifact in online EEG.
87. Development of measurement system for pronosupination of forearms and adopution of indexes for evaluation of the motion by machine learning.
88. The trend of magnetic applications in medical technology (2) - Magnetic technology in measurement of biological function -
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89. Model extension of the shape function fitting about the TMS artifact elimination .
90. The effects of rTMS and tDCS on the motor area to the mu rhythm .
91. Gamma-band frequency modulation in rat hippocampus during fixation .
92. Simultaneous EEG and NIRS measurements during sleep in preterm and term infants .
93. Evaluation of mental status using EEG・ECG・NIRS .
94. Evaluation system for pronation and supination of forearm .
95. The effects of rTMS and tDCS on the mu rhythm during motor imagery.
96. Analysis of Induced Gamma Band Response in EEG Using the Method Based on Band Power Method.
97. Analysis of Induced Gamma Band Response in EEG Using the Method Based on Band Power Method.
98. Selection and removal of artifacts in EEG based on independent components..
99. Effects of number of pulses of rTMS on the inter-reversal time of perceptual reversal.
100. Parameter Estimation in the Shape in the Sphere Description of TMS Artifact by the Equivalent Circuit Model.
101. Neuron Firing Statistics by Applying TMS using the Axon Model.
102. Effects to ERP by Low Frequency rTMS.
103. Effects of inhomogeneity in the brain tissue on the excitation threshold and sites in transcranial magnetic stimulation.
104. The change of electroencephalogram by repetitive transcranial magnetic stimulation.
105. Approximated Circuit Model of the TMS Artifact and Its Elimination.
106. Quantitative evaluation of pronation and supination movement of forearms using Wireless acceleration sensor.
107. The change of brain activity before and after the repetitive transcranial magnetic stimulation (rTMS).
108. The effect of repetitive transcranial magnetic stimulation to supramarginal gyrus on P300.
109. Measurement of P300 during Transcranial magnetic Stimulation.
110. Effects of TMS to the PPC on Visual Search Task.
111. Study of Visual Perception using Transcranial Magnetic Stimulation.
112. Possibility of Transcranial Magnetic Stimulation to Neuroscience and Clinical Application.
113. Effects of repetitive transcranial magnetic stimulation on perceptual reversal.
114. Differences in evoked EEG by Transcranial Magnetic Stimulation Applied to Motor and Posterior parietar Cortex.
115. A study of Perceptial reversals of Ambiguous Figures by Repetitive Transcranial magnetic Stimulation.
116. Temporal aspect on visual search task using transcranial magnetic stimulation.
117. Measure of EEG during Transcranial Magnetic Stimulation at various stimulus points.