Optimal peak area determination in the presence of noise

Abstract

A method is presented for determining optimal peak integration intervals on the basis of known peak shapes and noise characteristics. General theoretical considerations lead to conditions yielding optimal integration intervals. Examples of frequently occurring peak shapes and noise types are given, such as gaussian or skewed peak shapes, with band-limited first-order noise or flicker noise superimposed. The optimal integration intervals are approximately independent of the signal-to-noise ratio, and they are considerably smaller than the integration intervals normally used. The resulting expected peak area estimation errors are compared with the estimation error resulting from peak maximum amplitude measurement. On the basis of this comparison, rules of thumb are proposed to determine whether piak maximum measurement or peak integration yields the best results. Simulation of different peak shapes with noise superimposed confirms the results obtained. A flexible method is presented for the optimal measurement of the area of peaks with an unknown shape. This on-line method is simple, and could be used as a simple peak-finding procedure. The method requires almost no computer memory, and can be implemented on a microcomputer. A simulated example of this procedure is given.