Abstract
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.
Highlights
Asthma and chronic obstructive pulmonary disease (COPD) are common around the World.Because of air pollution and other environmental factors, the prevalence of asthma and COPD continues to grow
The proposed system was built as an independent wheezing detection silicon intellectual property (WDSIP), able to be integrated with other functional silicon intellectual properties (SIPs), e.g., universal asynchronous receiver/transmitter (UART), direct memory access (DMA), on system-on-programmable-chips (SoPCs) using the peripheral local bus (PLB) and MicroBlaze processor provided by Xilinx
As long as the operational timing of the WDSIP satisfies the requirements of the PLB communication protocol, MicroBlaze can be used to control the setting of the corresponding register on the memory map
Summary
Asthma and chronic obstructive pulmonary disease (COPD) are common around the World. Because of air pollution and other environmental factors, the prevalence of asthma and COPD continues to grow. Certain approaches have been used to extract wheezing features [12,13,14]; for example, classification models have been combined with algorithms [15,16,17,18], but this requires a large number of coefficients determined through training This requires immense computational resources, which are not available on portable devices. The proposed system was built as an independent wheezing detection silicon intellectual property (WDSIP), able to be integrated with other functional silicon intellectual properties (SIPs), e.g., universal asynchronous receiver/transmitter (UART), direct memory access (DMA), on system-on-programmable-chips (SoPCs) using the peripheral local bus (PLB) and MicroBlaze processor provided by Xilinx This allowed for greater portability and reduced system volume. In contrast to a customized IC, an FPGA can be modified repeatedly, and can be flexibly integrated with other SIPs
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