title: Technical quality evaluation of EEG recording based on electroencephalographers' knowledge.
abstract: The aim of this study is to develop a technical quality evaluation system of electroencephalogram (EEG) recording in order to acquire technically satisfactory EEG records, which may contribute to the accuracy improvement of EEG interpretation. In our developed system, the evaluation of EEG recording comprises the detection of technical artifacts and physiological status, which indicates the recording status objectively. In addition, the caution signals to users are generated in the system according to the undesired status detected. The information displayed to users includes the updated EEG records and instant evaluation results. Two examples of evaluation results are introduced in this paper, illustrating unsatisfactory records and artifact free records, respectively. The experimental results are proposed to verify the effectiveness of the technical quality evaluation of EEG recording. The implementation of the technical quality evaluation of EEG recording is helpful to acquire technically satisfactory EEG records, which may improve the accuracy of results in both the visual and the automatic EEG interpretation, and ease the laborious work of EEG technicians in the recording progress.
authors.affiliation: Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, Saga 840-8502, Japan.
authors.forename: Masatoshi
authors.initials: M
authors.lastname: Nakamura
authors.forename: Qian
authors.initials: Q
authors.lastname: Chen
authors.forename: Takenao
authors.initials: T
authors.lastname: Sugi
authors.forename: Akio
authors.initials: A
authors.lastname: Ikeda
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Shibasaki
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D011785:Quality Assurance, Health Care / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface