Takenao Sugi | PubMed Health

PubMed2005

Technical quality evaluation of EEG recording based on electroencephalographers' knowledge.

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.

Adult↗

PubMed2002

Adaptive EEG spike detection: determination of threshold values based on conditional probability.

Determination of the threshold value for automatic EEG spike detection was investigated adopting conditional probability. An adaptive spike detection method was constructed and evaluated. A discriminant function for detecting spikes was obtained by conditional probability calculated from the EEG spike data. The relationship among false-negatives, false-positives and threshold values for the discriminant function was investigated. An adaptive detection algorithm was developed by combining different threshold values. False-negative and false-positive rates for spike detection depended on the threshold values. The adaptive spike detection algorithm achieved a high detection rate and accuracy. The advantage of the proposed method is to construct an adaptive detection algorithm by combining the threshold values according to the purpose of spike detection. Since the threshold can be easily changed in the proposed method, it is practically effective for clinical use.

Adult↗