OBJECTIVES: The quantification of subtle patterns in sequential data, and their changes, has considerable potential utility throughout psychiatry, including the analyses of mood ratings, heart rate, respiratory, and electroencephalographic recordings. METHODS: Approximate entropy (ApEn), a relatively recently developed statistic quantifying serial irregularity, has been applied in numerous studies throughout mathematics and other fields of study, especially biology. RESULTS: We discussed applications of ApEn, both extant and potential, of most relevance to psychiatrists. We provided a mechanistic interpretation of lowered ApEn values, and discusses the relationship between ApEn and other (both classical and complexity) measures of serial dynamics. We also briefly discussed cross-ApEn, a thematically similar quantification of two-variable asynchrony that can aid in uncovering subtle disruptions in complicated network dynamics. CONCLUSIONS: ApEn and cross-ApEn have significant potential to consequentially enhance present statistical methodologies of analysis of psychiatric data, in both clinical and in research settings.
OBJECTIVES: The quantification of subtle patterns in sequential data, and their changes, has considerable potential utility throughout psychiatry, including the analyses of mood ratings, heart rate, respiratory, and electroencephalographic recordings. METHODS: Approximate entropy (ApEn), a relatively recently developed statistic quantifying serial irregularity, has been applied in numerous studies throughout mathematics and other fields of study, especially biology. RESULTS: We discussed applications of ApEn, both extant and potential, of most relevance to psychiatrists. We provided a mechanistic interpretation of lowered ApEn values, and discusses the relationship between ApEn and other (both classical and complexity) measures of serial dynamics. We also briefly discussed cross-ApEn, a thematically similar quantification of two-variable asynchrony that can aid in uncovering subtle disruptions in complicated network dynamics. CONCLUSIONS: ApEn and cross-ApEn have significant potential to consequentially enhance present statistical methodologies of analysis of psychiatric data, in both clinical and in research settings.
Authors: Olivier Darbin; Xingxing Jin; Christof Von Wrangel; Kerstin Schwabe; Atsushi Nambu; Dean K Naritoku; Joachim K Krauss; Mesbah Alam Journal: Int J Neural Syst Date: 2015-10-06 Impact factor: 5.866
Authors: Collin Y Liu; Anitha P Krishnan; Lirong Yan; Robert X Smith; Emily Kilroy; Jeffery R Alger; John M Ringman; Danny J J Wang Journal: J Magn Reson Imaging Date: 2012-12-07 Impact factor: 4.813