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1 TG3-1 28th Fuzzy System Symposium (Nagoya, An Investigation of EEG for eyes open and closed using a dry-electrode based mobile neuro-sensor Yoshihito Maki 1 Tsuyoshi Nakamura 2 Masayoshi Kanoh 3 Kouji Yamada 1 1 Nagoya Institute of Technology 2 2 Chukyo University 3 3 Institute of Advanced Media Arts and Sciences Abstract: Given a remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Supposing that humans coexist with robots, we expect to realize daily communication with robots and communication support by robots. To achieve that, robots have to have abilities that perception to perceive human s mental state or mood, and communication to communicate it. Regarding ability of perception, we had suggested the approach using single dry-electrode neuro-sensor of NeuroSky MindSet and experimented with it. As the result, by using the approach, the brain waves obtained from NeuroSky MindSet could discriminate subjects state with high accuracy. However, in the experiment the subjects state depended on both mental stress and eyes open/closed state and we did t clarify which factor determined the subjects state. This study investigated which of eyes open/closed or mental stress state gives some features to brain waves observed from B3 Band, The investigation suggests that eyes open/closed state has a lot of influence to the brain waves, and both NeuroSky MindSet and B3 Band can be used to estimate human s simple state such as eyes open/closed in daily life. 1 SSVEP( ) BCI [1, 2, 3, 4, 5, 6] 1 B3 Band 2 631

2 1 1 NeuroSky MindSet Bluetooth MindSet B3 Band( 2) MindSet [7] 2: B3 Band 1: NeuroSky MindSet NeuroSky MindSet MindSet 80% [8] 1 MindSet 2 B3 Band B3 Band MindSet MindSet NeuroSky MindSet B3 Band 512Hz 1 FFT SupportVectorMachine(SVM) SVM δ, θ, α l, α h, β l, β h, γ l, γ h 8 δ:0.5 3Hz θ:3 8Hz α l :8 10Hz α h :10 12Hz β l :12 20Hz β h :20 30Hz γ l :30 45Hz, γ h :45 60Hz 8 8 SVM δ θ 6 SVM 8 δ θ SVM 2 6 δ δ θ 8 SVM 6 SVM 8 M 8 = {δ, θ, α h, α l, β h, β l, γ h, γ l } 6 M 6 = {α h, α l, β h, β l, γ h, γ l } 1 5 M 8 t M 8 (t)

3 [6] M 8 (t) M 6 (t) 3 M 8 (t) = k=t+2 k=t 2 M 8 (k) k=t+2 1 T M 8 (k) k=t 2 B3 Band / B3 Band (relax) (calculate) B3 Band , (10 3 ) ( ) n n : time[sec] SVM SVM M 8 (t) M 6 (t) (relax calculate) 1 relax calculate SVM SVM SVM 2 3 SVM SVM SVM 2 4 4: SVM relax calculate 1 / 2 (open) (closed) / 2 SVM 1 SVM 2 633

4 SVM 2 5 open closed 5: SVM 7: 8 SVM 6 SVM 4 SVM B3 Band 2 8 SVM 6 SVM 2 SVM 6 7 8: 8 SVM 6 SVM 6: 8 SVM 6 SVM 6 7 SVM 50% B3 Band MindSet 80% 8 70% 8 SVM M 8 (t) δ ( ) δ SVM δ δ B3 Band δ 6 SVM B3 Band 634

5 識が有るか無いかなどの 2 状態を開眼/閉眼によって 波数帯を除いた場合でも 目の開閉のような単純な状 態推定ならば可能であると考えられる このことから 判別するような場合には十分有用だと考えられる ま B3 Band を用いる状況によっては 簡便な 2 状態判別 器として十分有効であることが期待される た 目の開閉の影響を大きく受けている脳波を除いて 行った判別でも 多少精度は落ちるものの比較的高い 精度で正しい判別が行えていたことから 従来の脳波 計には及ばないものの 簡易でモバイルなセンサとし ての利用価値は大いにあると考えられる このような性質から 1 点電極の脳波デバイスは 従 来の 電極のウェット型脳波デバイスから 1 点の みを取り出して利用していること等しいと推定される このことに関しては 類似した研究報告がされててお り 本実験の結果からもきわめて妥当な結果であると 言える [9, 10] しかしそうした場合に 従来の多電極 の脳波デバイスが眼球運動によって受ける δ 波干渉と 1 点電極の脳波デバイスが受ける目の開閉状態による δ 波干渉が 必ずしも同じであるとは言えない 本研 究の実験では 開眼と閉眼の状態の違いにより δ 波の パワーに大きな違いが見られたものの それが多電極 型デバイスを用いた先行研究にて報告されていた眼球 運動形成 δ によるものかどうかは あくまで我々の推 察に留まっている 今後は 1 点電極の脳波デバイス が多電極の脳波デバイスから 1 点だけ用いたものであ るという推定の上で 多電極の脳波デバイスで測定さ れた各点の脳波のパワーと 1 点電極の脳波デバイスの で測定したパワーとを比較し 関係性を調査する必要 があると考えられる 同時に 簡易な脳波センサが有 効だと思われる局面を想定して そうした局面での有 効性を調査していきたい また 今回の結果では 判 別率に個人差が見られた SVM の判別性能をより高く するために 脳波のパワースペクトル変化などを見な がら この個人差の要因について深く検討を行ってい く必要があると考える 図 9: 開眼時の時系列パワー比 M8 (t) 図 10: 閉眼時の時系列パワー比 M8 (t) 5 おわりに 参考文献 本稿では 日常生活の上で 人間共生型ロボットが [1] A. Luo, T. J. Sullivan : A user-friendly SSVEP based brain computer interface using a timedomain classifier, Journal of Neural Engineering, Vol.7, No.2, pp , インタラクション及びコミュニケーション支援を行え るようになることを目的とし 先行研究で着目されて いるモバイルな脳波デバイスを用いての人の心理状態 推定が 目の開閉によるノイズの影響無しに正しく推 定可能か否かについて調査を行った 実験結果から [2] G. Rebolledo-Mendez, I. Dunwell, E. A. Martı nez-miro n, M. D. Vargas-Cerda n, S. de Freitas, F. Liarokapis, A. R. Garcı a-gaona: Assessing Neurosky s Usability to Detect Attention Levels In An Assessment Exercise, Proceedings of the 13th International Conference MindSet や B3 Band のような 1 点ないし 2 点の電極 を使うドライ型センサは 目の開閉による筋電位の影 響を強く受けていると推測され この点については不 安定なデバイスであると思われる しかし 目の開閉などの単純な判別に用いるには十 分であり 日常生活の上で起きているか寝ているか 意 635

6 on Human-Computer Interaction. Part I: New Trends, pp , [3] E. Haapalainen, S. Kim, J. F. Forlizzi, A. K. Dey : Psycho-physiological measures for assessing cognitive load, Proceedings of the 12th ACM international conference on Ubiquitous computing Ubicomp 10, pp , [4] Eija Haapalainen, SeungJun Kim, Jodi F. Forlizzi, Anind K. Dey : Psycho-Physiological Measures for Assessing Cognitive Load, [5] Katie Crowley, Aidan Sliney, Ian Pitt, Dave Murphy : Evaluating a Brain-Computer Interface to Categorise Human Emotional Response, 10th IEEE International Conference on Advanced Learning Technologies, [6] Yoshitsugu Yasui : A Brainwave Signal Measurement and Data Processing Technique for Daily Life Applications Journal of Physiological Anthropology. [7] Jack Mostow, Kai-min Chang, and Jessica Nelso : Toward Exploiting EEG Input in a Reading Tutor, [8] Yoshihito Maki, Genma Sano, Yusuke Kobashi, Tsuyoshi Nakamura, Masayoshi Kanoh, Koji Yamada : Estimating Subjective Assessments using a Simple Biosignal Sensor. [9] Chin-Teng Lin, Lun-De Liao, Yu-Hang Liu, I- Jan Wang, Bor-Shyh Lin, Jyh-Yeong Chang : Novel Dry Polymer Foam Electrodes for Long- Term EEG Measurement, IEEE TRANSAC- TIONS ON BIOMEDICAL ENGINEERING, VOL. 58, NO. 5, [10] NeuroSky White Paper : Brainwave EEG Signal, maki@ai.nitech.ac.jp 636

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