生体磁気信号源の位置推定に関わる機械学習モデルの逆解析

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2024/04/01

タイトル(英語): Inverse Analysis of Machine Learning Models for Position Estimation of Biomagnetic Signal Sources

著者名: 熊谷　寛（北里大学医療衛生学部医療工学科臨床工学専攻），田村　鈴（北里大学医療衛生学部医療工学科臨床工学専攻）

著者名(英語): Hiroshi Kumagai (School of Allied Health Sciences, Kitasato University), Suzu Tamura (School of Allied Health Sciences, Kitasato University)

キーワード: 生体磁気信号，機械学習モデル，逆問題　　biomagnetic signal，machine learning model，inverse problem

要約(英語): Many aspects of how magnetic particles, particularly magnetite particles, are distributed in living organisms and how they affect brain function and neurodegenerative diseases remain unclear. There is an urgent need to develop new methods and techniques to non-invasively and highly accurately detect the presence of these magnetic particles and estimate their location. In this study, we adopted Nearest Neighbors as a machine learning algorithm and analyzed the inverse problem of the machine learning model to estimate the position of magnetic particles that are the source of biomagnetic signals. By arranging the magnetic sensors in three dimensions, the percentage of position estimation errors of 1 cm or less increased, even though there were only 8 magnetic sensors, and the average position estimation error per horizontal plane was approximately 8 mm. Since the resolution of conventional magnetoencephalography equipment is 5 to 7 mm, and measurements are performed using approximately 150 SQUID sensors, it is possible to improve position estimation accuracy by adjusting the placement conditions of the magnetic sensors.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.144 No.4 （2024） 特集Ⅰ：量子・情報・エレクトロニクスの医療/ヘルスケア応用　特集Ⅱ：電子回路関連技術

本誌掲載ページ: 301-308 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/144/4/144_301/_article/-char/ja/