Paper
30 December 2008 Capillary electrophoresis (CE) peak detection using a wavelet transform technique
Robert Stewart, Andrew Wee, David B. Grayden, Yonggang Zhu
Author Affiliations +
Proceedings Volume 7270, Biomedical Applications of Micro- and Nanoengineering IV and Complex Systems; 727012 (2008) https://doi.org/10.1117/12.813449
Event: SPIE Smart Materials, Nano- and Micro-Smart Systems, 2008, Melbourne, Australia
Abstract
Capillary Electrophoresis (CE) is a separation technique that can be used as a sample pre-treatment step in chemical analysis. When coupled with a detection technique, identification of chemical species can be performed on the basis of the elution signals. However, the sensor signals are often complicated by high signal noise, varying baseline and overlapping peaks. There is thus a need for a signal processing technique capable of robustly detecting peaks in acquired sensor data. Here, we report on an algorithm that utilises the Continuous Wavelet Transform (CWT) for the detection of analyte peaks. The algorithm that has been developed makes use of a wavelet equal to the first derivative of a Gaussian function and has been successfully applied to data obtained from a CCD sensor fabricated on a polymer microfluidic separation chip. The algorithm operates by taking the CWT of the sensor response. It then analyses patterns in the local maximum and minimum points evident across scales in the CWT coefficients to find the peaks in the time series data. The performance of two versions of the algorithm have been compared for synthetic data sets each with known baseline, peaks and noise. The improved algorithm has been shown to successfully find peaks with a high sensitivity and low False Discovery Rate within a range of sensitivities.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert Stewart, Andrew Wee, David B. Grayden, and Yonggang Zhu "Capillary electrophoresis (CE) peak detection using a wavelet transform technique", Proc. SPIE 7270, Biomedical Applications of Micro- and Nanoengineering IV and Complex Systems, 727012 (30 December 2008); https://doi.org/10.1117/12.813449
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Cited by 3 scholarly publications.
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KEYWORDS
Continuous wavelet transforms

Signal to noise ratio

Wavelets

Algorithm development

Detection and tracking algorithms

Capillaries

Sensors

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