Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

• Published in: Scientific reports Vol. 11; no. 1; pp. 304 - 9
• Main Authors: Yamanashi, Takehiko, Kajitani, Mari, Iwata, Masaaki, Crutchley, Kaitlyn J., Marra, Pedro, Malicoat, Johnny R., Williams, Jessica C., Leyden, Lydia R., Long, Hailey, Lo, Duachee, Schacher, Cassidy J., Hiraoka, Kazuaki, Tsunoda, Tomoyuki, Kobayashi, Ken, Ikai, Yoshiaki, Kaneko, Koichi, Umeda, Yuhei, Kadooka, Yoshimasa, Shinozaki, Gen
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 11.01.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/378/116; 692/53/2421; Algorithms; Data analysis; Delirium; EEG; Electroencephalography; Humanities and Social Sciences; Mental disorders; multidisciplinary; Science; Science (multidisciplinary)

Current methods for screening and detecting delirium are not practical in clinical settings. We previously showed that a simplified EEG with bispectral electroencephalography (BSEEG) algorithm can detect delirium in elderly inpatients. In this study, we performed a post-hoc BSEEG data analysis using...