Examination and it's evaluation of preprocessing method for individual identification in EEG

• Item type: Symposium(1)
• 公開日: 2018-10-31
• タイトル: Examination and it's evaluation of preprocessing method for individual identification in EEG
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: Kanazawa Institute of Technology,;Kanazawa Institute of Technology,
• 著者所属: Kanazawa Institute of Technology
• 著者所属(英): en
• 著者所属(英): Kanazawa Institute of Technology,;Kanazawa Institute of Technology,
• 著者所属(英): en
• 著者所属(英): Kanazawa Institute of Technology
• 著者名: Masato, Yamashita; Minoru, Nakazawa; Yukinobu, Nishikawa
• 著者名(英): Masato, Yamashita; Minoru, Nakazawa; Yukinobu, Nishikawa
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In recent years, techniques of Brain Machine Interface (BMI) which conducts human communication and robot manipulation using human brain activity are widely researched. This is the result of a noninvasive electroencephalograph device that can measure Electroencephalogram (EEG) in real time. However, there is a present condition that the authentication method when BMI is not much researched. In our research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this paper, we construct and then evaluate a system that performs biometric authentication using EEG at image stimulus. We perform feature extraction using cross-correlation coefficient, and Support Vector Machine (SVM) for classification / authentication. And We considered the method for preprocessing (digital filter, artifact countermeasure, epoch), we verify more appropriate preprocessing method. We verified the proposed method. In our proposed system , Equal Error Rate(EER) : 2.0% was obtained when artifact countermeasure, digital filter (IIR filter), and epoch method were used. From the result of False Acceptance Rate (FAR) and False Rejection Rate (FRR), our system was suggested that accuracy is improved by taking artifact countermeasure.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In recent years, techniques of Brain Machine Interface (BMI) which conducts human communication and robot manipulation using human brain activity are widely researched. This is the result of a noninvasive electroencephalograph device that can measure Electroencephalogram (EEG) in real time. However, there is a present condition that the authentication method when BMI is not much researched. In our research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this paper, we construct and then evaluate a system that performs biometric authentication using EEG at image stimulus. We perform feature extraction using cross-correlation coefficient, and Support Vector Machine (SVM) for classification / authentication. And We considered the method for preprocessing (digital filter, artifact countermeasure, epoch), we verify more appropriate preprocessing method. We verified the proposed method. In our proposed system , Equal Error Rate(EER) : 2.0% was obtained when artifact countermeasure, digital filter (IIR filter), and epoch method were used. From the result of False Acceptance Rate (FAR) and False Rejection Rate (FRR), our system was suggested that accuracy is improved by taking artifact countermeasure.
• 書誌情報: 第26回マルチメディア通信と分散処理ワークショップ論文集; p. 30-35, 発行日 2018-10-31
• 出版者 / 言語: ja
• 出版者: 情報処理学会