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- W2182279498 abstract "ECG analysis continues to be a vital part of drug and device discovery especially in the cardiovascular franchise. Various parameters derived from the ECG waveform such as the P-R, Q-T, R-R, Q-R-S and S-T intervals, and heart rate variability serve as safety and efficacy endpoints for many clinical trials. The detection of the R-peak and the QRS complex in the ECG is an important step in deriving these endpoints. A number of algorithms based on time and frequency domains are available for detecting various aspects of the ECG waveform. ECG features are routinely identified in core labs using algorithms implemented in C, MATLAB ® , and other languages. This paper explores the implementation of ECG R-peak detection using SAS ® . The ECG data that is used for analysis and reporting in clinical trials is usually preprocessed. Implementing an ECG feature detection algorithm in-house using SAS ® provides the flexibility to perform exploratory analysis of parameters derived from the ECG. Further, it allows the programmer or researcher to analyze the same data from exploratory perspective. Also when ECG based parameters are used as primary endpoints, it enhances the transparency of pharmaceutical and medical device companies while submitting SAS ® code and data to regulatory agencies." @default.
- W2182279498 created "2016-06-24" @default.
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- W2182279498 date "2010-01-01" @default.
- W2182279498 modified "2023-09-27" @default.
- W2182279498 title "ECG Feature Detection Using SAS" @default.
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