APPLICATION OF WALSH TRANSFORM BASED METHOD ON TRACHEAL BREATH SOUND SIGNAL SEGEMENTATION Jin Feng, Farook Sattar School of Electrical& Electronic Engineering, Nanyang Technological University, Singapore Moe Pwint Dept. of Information Science, The University of Computer Studies, Yangon, Myanmar Keywords: Segmentation, Walsh Transform, Refinement Scheme, Inspiratory/Expiratory Phase, Various Types of Tra- cheal Breath Sounds, End-Inspiratory/Expiratory Pause. Abstract: This paper proposes a robust segmentation method for differentiating consecutive inspiratory/expiratory episodes of different types of tracheal breath sounds. This has been done by applying minimal Walsh ba- sis functions to transform the original input respiratory sound signals. Decision module is then applied to differentiate transformed signal into respiration segments and gap segments. The segmentation results are improved through a refinement scheme by new evaluation algorithm which is based on the duration of the seg- ment. The results of the experiments, which have been carried out on various types of tracheal breath sounds, show the robustness and effectiveness of the proposed segmentation method. 1 INTRODUCTION For early detection of diverse illnesses, accurate es- timation of respiratory rate is very important (Sierra et al., 2005). Many adventitious lung sounds, which are indications of infectious and respiratory diseases, can be clinically characterized by their duration in respiratory cycle and relationship to the phase of res- piration (Meslier et al., 1995). Therefore, segmenta- tion of respiratory sound into individual respiratory cycles and further subdividing into its inspiratory and expiratory phases is necessary in quantifying adventi- tious sounds. Generally, phonopneumography or spirometer to- gether with sound recording devices are always used in respiratory sound analysis, in which amplitude of the sound signal is displayed simultaneously with the airflow as a function of time. Signals can be segmented into consecutive inspiratory phase, end-inspiratory pause, expiratory phase, and end- expiratory phase according to the provided Forced Expiratory Volume (FEV) readings (Taplidou and Hadjileontiadis, 2007)(Cort ´ es et al., 2005). However, it could be difficult to carry out a spirometric test for patients with high obstruction in tracheal (Cort ´ es et al., 2005). Acoustical flow estimation is one of the first at- tempts to relate respiratory sounds and flow. In (Hos- sain and Moussavi, 2002) and (Golabbakhsh, 2004), airflow has been estimated using the respiratory sounds by applying different models, while exponen- tial model between flow and averaged sound power has been found with the highest estimation accu- racy. The model coefficients calculation in the above mentioned methods require samples of breath sound with known flow. However, the calibration process is not always possible. Therefore, a modified entropy- based linear model describing relationship between flow and tracheal sound has been derived in (Yadol- lahi and Moussavi, 2006) without prior acoustical flow knowledge. Also, other segmentation methods using spectral and temporal analysis of transformed respiratory sounds have been developed in (Hult et al., 2000)(Sierra et al., 2004). As these researches are still in preliminary stage, the segmentation is restricted to normal tracheal breath and the accuracy depends mainly on signal-to-noise ratio (SNR) for various types of tracheal breath sounds. In this paper, an automatic and robust respiratory sound signal segmentation method is developed. The proposed method is based on the modification of input sound signal using a modified analysis and synthesis 116 Feng J., Sattar F. and Pwint M. (2008). APPLICATION OF WALSH TRANSFORM BASED METHOD ON TRACHEAL BREATH SOUND SIGNAL SEGEMENTATION. In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing, pages 116-121 DOI: 10.5220/0001057501160121 Copyright c  SciTePress