论文信息 - Approximate entropy and its preliminary application in the field of EEG and cognition

Approximate entropy and its preliminary application in the field of EEG and cognition

Approximate Entropy (ApEn) is a newly introduced statistic that can be used to quantify the complexity (or irregularity) of a time series. A practical fast algorithm of ApEn is proposed in this article and two experimental results in the field of EEG and cognition are presented.

Hong Bo | Yang Fusheng | Tin-Cheung Chan | Tang Qingyu

[1] Milan Palus,et al. Coarse-grained entropy rates for characterization of complex time series , 1996 .

[2] S M Pincus,et al. Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[3] Steven M. Pincus,et al. Older males secrete luteinizing hormone and testosterone more irregularly, and jointly more asynchronously, than younger males. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[4] D Sapoznikov,et al. Detection of regularities in heart rate variations by linear and non-linear analysis: power spectrum versus approximate entropy. , 1995, Computer methods and programs in biomedicine.

[5] S M Pincus,et al. Greater signal regularity may indicate increased system isolation. , 1994, Mathematical biosciences.

[6] A L Goldberger,et al. Physiological time-series analysis: what does regularity quantify? , 1994, The American journal of physiology.

[7] M L Johnson,et al. Differential impact of age, sex steroid hormones, and obesity on basal versus pulsatile growth hormone secretion in men as assessed in an ultrasensitive chemiluminescence assay. , 1995, The Journal of clinical endocrinology and metabolism.

[8] G G Haddad,et al. Heart rate control in normal and aborted-SIDS infants. , 1993, The American journal of physiology.