Next Article in Journal
Reliability, Validity, and Significance of Assessment of Sense of Contribution in the Workplace
Next Article in Special Issue
Gait Recognition and Walking Exercise Intensity Estimation
Previous Article in Journal
Diffusion of Nitrogen and Phosphorus Across the Sediment-Water Interface and In Seawater at Aquaculture Areas of Daya Bay, China
Previous Article in Special Issue
Detection of Potential Drug-Drug Interactions for Outpatients across Hospitals
Open AccessArticle

An FPGA-Based Rapid Wheezing Detection System

Department of Computer Science and Information Engineering, National Taipei University, No. 151, University Road, Sanshia District, New Taipei 23741, Taiwan
Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2014, 11(2), 1573-1593;
Received: 30 December 2013 / Revised: 24 January 2014 / Accepted: 24 January 2014 / Published: 29 January 2014
Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. View Full-Text
Keywords: rapid wheezing detection; field-programmable gate array (FPGA); spectrogram image processing; support vector machine (SVM) rapid wheezing detection; field-programmable gate array (FPGA); spectrogram image processing; support vector machine (SVM)
Show Figures

Figure 1

MDPI and ACS Style

Lin, B.-S.; Yen, T.-S. An FPGA-Based Rapid Wheezing Detection System. Int. J. Environ. Res. Public Health 2014, 11, 1573-1593.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

Only visits after 24 November 2015 are recorded.
Back to TopTop