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Yongbo Liang
Researcher at Guilin University of Electronic Technology
Publications - 22
Citations - 1113
Yongbo Liang is an academic researcher from Guilin University of Electronic Technology. The author has contributed to research in topics: Photoplethysmogram & Computer science. The author has an hindex of 11, co-authored 18 publications receiving 511 citations. Previous affiliations of Yongbo Liang include Central South University & University of British Columbia.
Papers
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Journal ArticleDOI
The use of photoplethysmography for assessing hypertension
Mohamed Elgendi,Richard Fletcher,Yongbo Liang,Newton Howard,Nigel H. Lovell,Derek Abbott,Kenneth Lim,Rabab K. Ward +7 more
TL;DR: Although the technology is not yet mature, it is anticipated that in the near future, accurate, continuous BP measurements may be available from mobile and wearable devices given their vast potential.
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An optimal filter for short photoplethysmogram signals
TL;DR: The aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered P PG signal using the skewness quality index.
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A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China.
TL;DR: This dataset can be used to carry out the study of photoplethysmograph (PPG) signal quality evaluation and to explore the intrinsic relationship between the PPG waveform and cardiovascular disease to discover and evaluate latent characteristic information contained in PPG signals.
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Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification.
TL;DR: A deep learning method for the classification and evaluation of hypertension using photoplethysmography (PPG) signals based on the continuous wavelet transform and pretrained convolutional neural network achieved higher accuracy when compared to the classical signal processing and feature extraction method.
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Hypertension Assessment via ECG and PPG Signals: An Evaluation Using MIMIC Database.
TL;DR: A novel hypertension management method based on arterial wave propagation theory and photoplethysmography (PPG) morphological theory was researched to explore the physiological changes in different blood pressure (BP) levels, and PPG features were shown to classify BP categories more accurately than PAT.