A Deep Learning Approach to Predict Blood Pressure from PPG Signals

@article{Tazarv2021ADL,
  title={A Deep Learning Approach to Predict Blood Pressure from PPG Signals},
  author={Ali Tazarv and Marco Levorato},
  journal={2021 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year={2021},
  pages={5658-5662}
}
  • Ali Tazarv, M. Levorato
  • Published 30 July 2021
  • Computer Science, Engineering, Medicine
  • 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Blood Pressure (BP) is one of the four primary vital signs indicating the status of the body’s vital (life-sustaining) functions. BP is difficult to continuously monitor using a sphygmomanometer (i.e. a blood pressure cuff), especially in everyday-setting. However, other health signals which can be easily and continuously acquired, such as photoplethysmography (PPG), show some similarities with the Aortic Pressure waveform. Based on these similarities, in recent years several methods were… 

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References

SHOWING 1-10 OF 26 REFERENCES
Features Extraction for Cuffless Blood Pressure Estimation by Autoencoder from Photoplethysmography
TLDR
This study focuses on the autoencoder which can extract complex features and can add new features of the pulse waveform for estimating the BP and shows that the correlation coefficients and the standard deviation of the difference between the measured BP and the estimated BP got improved.
CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment
TLDR
A novel deep learning framework (CorNET) to efficiently estimate heart rate (HR) information and perform biometric identification (BId) using only a wrist-worn, single-channel PPG signal collected in ambulant environment is presented.
A SVM Method for Continuous Blood Pressure Estimation from a PPG Signal
TLDR
A Support Vector Machine (SVM) method for continuous blood pressure estimation from a PPG Signal shows better accuracy than the linear regression method and also shows better accuracies than the ANN method in diastolic blood pressure, which brings great significance in the field of mobile wearable.
A feature exploration methodology for learning based cuffless blood pressure measurement using photoplethysmography
TLDR
Using the proposed light-weight features, the proposed predictors can successfully achieve a Grade A in two standards proposed by the American National Standards of the Association for the Advancement of Medical Instrumentation (AAMI) and British Hypertension Society (BHS).
A Novel Continuous Blood Pressure Estimation Approach Based on Data Mining Techniques
  • Fen Miao, Nan Fu, +4 authors Ye Li
  • Mathematics, Medicine
    IEEE Journal of Biomedical and Health Informatics
  • 2017
TLDR
The proposed approach is superior to the state-of-the-art PTT-based model for an approximately 2-mmHg reduction in the standard derivation at different time intervals, thus providing potentially novel insights for cuffless BP estimation.
Cuff-less PPG based continuous blood pressure monitoring - A smartphone based approach
TLDR
A novel method to extract a comprehensive set of features by combining PPG signal based and Heart Rate Variability related features using a single PPG sensor is proposed, which will open new avenues towards development of pervasive and continuous BP monitoring systems leading to an early detection and prevention of cardiovascular diseases.
Optical blood pressure estimation with photoplethysmography and FFT-based neural networks.
TLDR
A beat-to-beat optical blood pressure estimation paradigm using only photoplethysmogram (PPG) signal from finger tips is introduced and validated, which is fast and robust, and can potentially be used to perform pulse wave analysis in addition to BP estimation.
Cuff-less high-accuracy calibration-free blood pressure estimation using pulse transit time
TLDR
A novel method is proposed for accurate and reliable estimation of blood pressure that is calibration-free by extraction of several physiological parameters from Photoplethysmography (PPG) signal as well as utilizing signal processing and machine learning algorithms.
Continuous blood pressure monitoring during exercise using pulse wave transit time measurement
TLDR
It is shown that with the correct personal calibration it is possible to estimate the beat to beat systolic arterial blood pressure during the exercise with comparable accuracy to conventional noninvasive methods.
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