Design and implementation of a pulse wave generator based on Windkessel model using field programmable gate array technology. (July 2017)

• Record Type: Journal Article
• Authors: Wang, Lu; Xu, Lisheng; Zhou, Shuran; Wang, Hao; Yao, Yang; Hao, Liling; Li, Bing Nan; Qi, Lin
• Is Part Of: Biomedical signal processing and control. Volume 36(2017)
• Page Start: 93
• Page End: 101
• Publication Date: 2017-07
• Subjects: FPGA -- Pulse wave -- Runge-Kutta method -- SoPC -- Windkessel model; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.03.008
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The generator can generate any desired pulse waveforms corresponding to different physiological and pathological states. The Windkessel model is implemented with Field Programmable Gate Array (FPGA) for efficiency, portability and scalability. The critical parameters are flexible to be modulated according to the requirement of the users. It is possible to add different types of noises with varying signal-to-noise ratios. Abstract: Purpose: Pulse wave contains plenty of physiological and pathological information of cardiovascular system. There have been many commercial products that can analyze pulse wave signals for the quantification of cardiovascular functions. However, their performance often varies from case to case. It is thus necessary to generate typical pulse waveforms in order to quantitatively evaluate these commercial products. Methods: A pulse wave generator based on the Windkessel model is designed and implemented in this study because Windkessel model can describe the general features of a pulse wave with physiologically interpretable parameters that can be easily set by users. The numerical solutions are obtained by using the Runge-Kutta method. Results: The features of this work include: (1) the critical parameters are flexible to be modulated so that different pulse waveforms representing different states of the cardiovascular system could be simulated; (2) it is possible to add different types of noises with varying signal-to-noise ratios; (3) the software is designed under the System-on-a-Programmable-Chip (SoPC) developing flow; (4) the platform is implemented on Field Programmable Gate Array (FPGA) for efficiency, portability and scalability. Conclusion and significance: The pulse waves generated by the designed generator are quite similar to these measured in clinic. The new pulse wave generator is useful to test and evaluate various pulse wave analysis devices. It is also useful for the training of hospital personnel and young students.