Improved Principal Component Analysis for Anomaly Detection: Application to an Emergency Department
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Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionEnvironmental Statistics Group
Statistics Program
Date
2015-07-05Online Publication Date
2015-07-05Print Publication Date
2015-10Permanent link to this record
http://hdl.handle.net/10754/559088
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Monitoring of production systems, such as those in hospitals, is primordial for ensuring the best management and maintenance desired product quality. Detection of emergent abnormalities allows preemptive actions that can prevent more serious consequences. Principal component analysis (PCA)-based anomaly-detection approach has been used successfully for monitoring systems with highly correlated variables. However, conventional PCA-based detection indices, such as the Hotelling’s T2T2 and the Q statistics, are ill suited to detect small abnormalities because they use only information from the most recent observations. Other multivariate statistical metrics, such as the multivariate cumulative sum (MCUSUM) control scheme, are more suitable for detection small anomalies. In this paper, a generic anomaly detection scheme based on PCA is proposed to monitor demands to an emergency department. In such a framework, the MCUSUM control chart is applied to the uncorrelated residuals obtained from the PCA model. The proposed PCA-based MCUSUM anomaly detection strategy is successfully applied to the practical data collected from the database of the pediatric emergency department in the Lille Regional Hospital Centre, France. The detection results evidence that the proposed method is more effective than the conventional PCA-based anomaly-detection methods.Citation
Improved Principal Component Analysis for Anomaly Detection: Application to an Emergency Department 2015 Computers & Industrial EngineeringPublisher
Elsevier BVAdditional Links
http://linkinghub.elsevier.com/retrieve/pii/S036083521500279Xae974a485f413a2113503eed53cd6c53
10.1016/j.cie.2015.06.020