Using methods of time series data mining to recognize the influences of environmental factors on epileptic seizures. (May 2018)

• Record Type: Journal Article
• Authors: Lin, Jhe-Nan; Yang, Fu-Yi; Sun, Wei-Zen; Yang, Meng-Han
• Is Part Of: Computers & electrical engineering. Volume 68(2018)
• Page Start: 437
• Page End: 446
• Publication Date: 2018-05
• Subjects: Correlation measure -- EEMD -- Environmental factor -- Epileptic seizure -- FGD -- Statistical test; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.04.020
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: This research investigated whether environmental factors are important triggers for epileptic seizures. Epilepsy is a very common neurological disease whose exact pathology remains unknown. Numerous studies have observed that environmental changes can be important triggers for various illnesses. Incorporating a nationwide dataset, environmental factors were characterized as inducers for epilepsy using conventional methods and a recently-proposed algorithm of time series data mining. From iterative verification using these algorithms, epilepsy incidence increments were established in January and February of each year. Furthermore, epilepsy incidence was positively correlated with atmospheric pressure, and negatively correlated with ambient temperature. In summary, environmental factors might be important triggers for epilepsy, and the mined epidemiological properties are expected to be helpful for management of this disease.