INTERNATIONAL JOURNAL OF COMPUTER APPLICATION ISSUE 2, VOLUME 4 (AUGUST 2012) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797 Page 251 Pre-processing of PPG Signal with Performance based Methods Akash Kumar Bhoi 1 , Swarup Sarkar 2 , Purnendu Mishra 3 , Gyanesh Savita 4 1,2,4 Department of AE&I Engg, Sikkim Manipal Institute of Technology (SMIT), Majitar 3 Department of ECE, Vikash College of Engineering for Women, Bargarh Email: 1 akash730@gmail.com, 2 swarupsarkar2009@gmail.com, 3 purnendumish@gmail.com 4 gyanesh.savita@gmail.com ABSTRACT Analyzing PPG signals carefully can give us information related to diabetes and arthritis patient, because in their case there is a difference in the pulse shape changes as a function of disease which can be well observed visually. Photoplethysmography is a non- invasive technique that measures relative blood volume changes in the blood vessels close to the skin. We present the results of analysis of photoplethysmography (PPG) signals having motion artefacts which are as like Gaussian noise in nature with baseline drift. This paper discusses a methodology to analysis the performance of moving average algorithm (MAA) for baseline drift removal and noise cancellation with the help of wavelet transformation by „db4‟ wavelet. The results obtained are efficient and accurate. The decomposition levels during filtering process also analyzed. Key words: PPG Signal, Gaussian noise, baseline drift, noise cancellation, MAA, db4 wavelet Corresponding Author: Akash Kumar Bhoi INTRODUCTION Photoplethysmography (PPG) is an optical measurement technique that can be used to detect blood volume changes in the microvascular bed of a tissue [1]. The basic form of PPG technology requires only a few opto-electronic components: a light source to illuminate the tissue (e.g. skin), and a photodetector to measure the small variations in light intensity associated with changes in perfusion in the catchment volume. PPG is most often employed non-invasively and operates in the red region or in the near infrared region. The most recognized waveform feature is the peripheral pulse, and it is synchronized to each heartbeat. Despite its simplicity the origins of the different components of the PPG signal are still not fully understood. It is generally accepted, however, that they can provide valuable information about the cardiovascular system [2]. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques [3]. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular diseases.