Non-invasive continuous blood pressure measurement based on mean impact value method, BP neural network, and genetic algorithm

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
Xia TanYadan Zhang

Abstract

Non-invasive continuous blood pressure monitoring can provide an important reference and guidance for doctors wishing to analyze the physiological and pathological status of patients and to prevent and diagnose cardiovascular diseases in the clinical setting. Therefore, it is very important to explore a more accurate method of non-invasive continuous blood pressure measurement. To address the shortcomings of existing blood pressure measurement models based on pulse wave transit time or pulse wave parameters, a new method of non-invasive continuous blood pressure measurement - the GA-MIV-BP neural network model - is presented. The mean impact value (MIV) method is used to select the factors that greatly influence blood pressure from the extracted pulse wave transit time and pulse wave parameters. These factors are used as inputs, and the actual blood pressure values as outputs, to train the BP neural network model. The individual parameters are then optimized using a genetic algorithm (GA) to establish the GA-MIV-BP neural network model. Bland-Altman consistency analysis indicated that the measured and predicted blood pressure values were consistent and interchangeable. Therefore, this algorithm is of great significance to promo...Continue Reading

References

Nov 1, 1994·Journal of Clinical Engineering·K G Ng, C F Small
Apr 1, 1963·IEEE Transactions on Bio-medical Engineering·G L PRESSMAN, P M NEWGARD
Nov 12, 2013·Bio-medical Materials and Engineering·Fang Wang, Zhong Ji

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Citations

Jun 5, 2021·Medical & Biological Engineering & Computing·Nishigandha Dnyaneshwar Agham, Uttam M Chaskar
Aug 21, 2021·Computational Intelligence and Neuroscience·Hai Wang, Hongtao Zhang

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Software Mentioned

MATLAB
MIVs
TANSIG
MIV
Nets0 NETs0 Netd0 NETd0
PURELIN

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