Abstract
Some cardiovascular diseases (CVD) can be characterized by abnormalities in the blood pressure (BP) waveform. This work explores the use of ML techniques in a screening system currently under development for detection of BP waveform abnormalities - Bisferiens and Alternans pulses. The system uses a tonometric probe for signal acquisition, signal processing involving period segmentation and image processing, and classification. The classification method used was the support vector machine (SVM) and it achieved an accuracy of 99.84%. Signal acquisition is done locally and sent to a remote server where the signal and image processing and classification is performed and the result prediction is sent back to the user.
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References
WHO: Cardiovascular diseases (CVDs) May 2017. http://www.who.int/mediacentre/factsheets/fs317/en/
Sun, J., Reisner, A., Mark, R.: A signal abnormality index for arterial blood pressure waveforms. In: Computers in Cardiology 2006. IEEE, pp. 13–16 (2006)
Sun, J., Reisner, A., Saeed, M., Mark, R.: Estimating cardiac output from arterial blood pressurewaveforms: a critical evaluation using the mimic II database. In: Computers in Cardiology 2005. IEEE, pp. 295–298 (2005)
Zong, W., Heldt, T., Moody, G.B., Mark, R.G.: An open-source algorithm to detect onset of arterial blood pressure pulses. In: Computers in Cardiology 2003, pp. 259–262, Sept 2003
Luo, S., Zhou, J., Duh, H.B.-L., Chen, F.: BVP feature signal analysis for intelligent user interface. In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, ser. CHI EA 2017. ACM, pp. 1861–1868, New York (2017). https://doi.org/10.1145/3027063.3053121
Almeida, V.G., Vieira, J., Santos, P., Pereira, T., Pereira, H.C., Correia, C., Pego, M., Cardoso, J.: Machine learning techniques for arterial pressure waveform analysis. J. Personal. Med. 3(2), 82–101 (2013). http://www.mdpi.com/2075-4426/3/2/82
Webster, J.G., Hendee, W.R.: Encyclopedia of medical devices and instrumentation, volumes 1–4, Physics Today, vol. 42, p. 76 (1989)
Riojas, C.M., Dodge, A., Gallo, D.R., White, P.W.: Aortic dissection as a cause of pulsus bisferiens: a case report and review. Ann. Vasc. Surg. 30, 305-e1 (2016)
Euler, D.E.: Cardiac alternans: mechanisms and pathophysiological significance. Cardiovasc. Res. 42(3), 583–590 (1999)
Mikolajczyk, K., Schmid, C., Zisserman, A.: Human detection based on a probabilistic assembly of robust part detectors. In: Computer Vision - ECCV 2004, pp. 69–82 (2004)
Ronfard, R., Schmid, C., Triggs, B.: Learning to parse pictures of people. In: European Conference on Computer Vision. Springer, Heidelberg, pp. 700–714 (2002)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2005, CVPR 2005, vol. 1. IEEE, pp. 886–893 (2005)
Pereira, C.R., Weber, S.A., Hook, C., Rosa, G.H., Papa, J.P.: Deep learning-aided Parkinson’s disease diagnosis from handwritten dynamics. In: 2016 29th SIBGRAPI Conference on Graphics Patterns and Images (SIBGRAPI). IEEE, pp. 340–346 (2016)
Matlab signal processing toolbox 2017b
Tan, P.-N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison-Wesley Longman Publishing Co., Inc., Boston (2005)
Acknowledgment
Authors gratefully acknowledge the funding of Project NORTE-01-0145-FEDER-000022 - SciTech - Science and Technology for Competitive and Sustainable Industries, cofinanced by Programa Operacional Regional do Norte (NORTE2020), through Fundo Europeu de Desenvolvimento Regional (FEDER). This work was also funded by Project LAETA - UID/EMS/50022/2013.
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Nogueira, D., Tavares, R., Abreu, P., Restivo, M.T. (2019). Demonstration: Online Detection of Abnormalities in Blood Pressure Waveform: Bisfiriens and Alternans Pulse. In: Auer, M., Langmann, R. (eds) Smart Industry & Smart Education. REV 2018. Lecture Notes in Networks and Systems, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-95678-7_60
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DOI: https://doi.org/10.1007/978-3-319-95678-7_60
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