A recursive algorithm to compute the baseline drift in recorded biological signals.
Baseline estimation and removal is one of the main problems to overcome in order to obtain a correct interpretation of recorded biological signals. The method described in this paper is based on a new application of recursive estimation of a smoothing spline, selected to model the unknown baseline. Its advantages over conventional methods derive from these characteristics: it is parametric and recursive, it works in the time domain, and the same software can be used in different applications, since no a priori frequency knowledge is needed. In the example, the method is applied to ECG recordings and a spectral analysis is thereby shown.
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Istituto per le Applicazioni del Calcolo M. Picone, Consiglio Nazionale delle Richerche, Rome, Italy.
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D000465:Algorithms; D002138:Calibration; D004562:Electrocardiography / Q000379:methods; D006801:Humans; D008432:Mathematical Computing; D012815:Signal Processing, Computer-Assisted