Smith Waterman法を利用した fNIRS データの類似部分抽出システムの提案と評価

概要

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One of non-invasive brain functional mapping equipments fNIRS (functional Near-Infrared Spectroscopy) is known for its practicality. One of the characteristics of fNIRS is that fNIRS derives enormous time series data in each experiment, so that it is hard to analyze these data effectively. In this paper, we introduce the novel algorithm which can extract similar subsequence of fNIRS data. In the proposed algorithm, the conventional homology search and Smith Waterman method are applied. Since there are several software libraries of these algorithms, the proposed algorithm is not only useful for getting satisfactory results but also effective for drawing these results quickly. In this paper, the fNIRS data analysis system is illustrated, where the proposed algorithm has been implemented. Using the proposed system, the effectiveness of the proposed algorithm is discussed, and the response time of the system is estimated and illustrated.