An FPGA System for Rapid Wheezing Detection

碩士 === 國立臺灣大學 === 生醫電子與資訊學研究所 === 99 === Wheezes have often been treated as an important indicator to diagnose the obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to analyze and to long-term monitor the patients’ situations. This thesis proposes a portable wheez...

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Main Authors: Tian-Shiue Yen, 嚴天斈
Other Authors: 張璞曾
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/8bx39y
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spelling ndltd-TW-099NTU051140122019-07-11T03:42:16Z http://ndltd.ncl.edu.tw/handle/8bx39y An FPGA System for Rapid Wheezing Detection 基於FPGA的快速哮鳴音偵測系統 Tian-Shiue Yen 嚴天斈 碩士 國立臺灣大學 生醫電子與資訊學研究所 99 Wheezes have often been treated as an important indicator to diagnose the obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to analyze and to long-term monitor the patients’ situations. This thesis proposes a portable wheezing detection system based on Field Programmable Gate Array (FPGA). It accelerates wheezes detection. It could flexibility function as a single process system or be integrated with other biomedical signal detection system. Firstly, the sound signal is segmented into units of 2 seconds. Then short-time Fourier transform was used to look into the relationship between the time and frequency components of the sound data. Thereafter, we continued processing the spectrogram by 2D bilateral filtering, edge detection, multi-threshold image segmentation, morphological image processing and image labeling to extract the wheezes features according to Computerized Respiratory Sound Analysis (CORSA) standards. Then these features were used to train Support Vector Machines (SVMs) and built the classification models. Finally, this trained model is used to distinguish to detect wheeze for new coming sound data. This system runs on Xilinx ML605 platform. Experiment results show a high performance of 0.912 in analysis of wheeze recognition in hardware. The detection process is good for 51.97 MHz clock frequency. It is good for high speed classification for wheeze. 張璞曾 2011 學位論文 ; thesis 120 en_US
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description 碩士 === 國立臺灣大學 === 生醫電子與資訊學研究所 === 99 === Wheezes have often been treated as an important indicator to diagnose the obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to analyze and to long-term monitor the patients’ situations. This thesis proposes a portable wheezing detection system based on Field Programmable Gate Array (FPGA). It accelerates wheezes detection. It could flexibility function as a single process system or be integrated with other biomedical signal detection system. Firstly, the sound signal is segmented into units of 2 seconds. Then short-time Fourier transform was used to look into the relationship between the time and frequency components of the sound data. Thereafter, we continued processing the spectrogram by 2D bilateral filtering, edge detection, multi-threshold image segmentation, morphological image processing and image labeling to extract the wheezes features according to Computerized Respiratory Sound Analysis (CORSA) standards. Then these features were used to train Support Vector Machines (SVMs) and built the classification models. Finally, this trained model is used to distinguish to detect wheeze for new coming sound data. This system runs on Xilinx ML605 platform. Experiment results show a high performance of 0.912 in analysis of wheeze recognition in hardware. The detection process is good for 51.97 MHz clock frequency. It is good for high speed classification for wheeze.
author2 張璞曾
author_facet 張璞曾
Tian-Shiue Yen
嚴天斈
author Tian-Shiue Yen
嚴天斈
spellingShingle Tian-Shiue Yen
嚴天斈
An FPGA System for Rapid Wheezing Detection
author_sort Tian-Shiue Yen
title An FPGA System for Rapid Wheezing Detection
title_short An FPGA System for Rapid Wheezing Detection
title_full An FPGA System for Rapid Wheezing Detection
title_fullStr An FPGA System for Rapid Wheezing Detection
title_full_unstemmed An FPGA System for Rapid Wheezing Detection
title_sort fpga system for rapid wheezing detection
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/8bx39y
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