A survey: From shallow to deep machine learning approaches for blood pressure estimation using biosensors-Reference-Cited by-同舟云学术

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A survey: From shallow to deep machine learning approaches for blood pressure estimation using biosensors

Published:2022-07 Issue: Volume:197 Page:116788
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Maqsood Sumbal,Xu Shuxiang,Tran Son,Garg Saurabh,Springer Matthew,Karunanithi Mohan,Mohawesh Rami

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference148 articles.

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2. Photoplethysmography and its application in clinical physiological measurement;Allen;Physiological measurement,2007

3. Modelling the relationship between peripheral blood pressure and blood volume pulses using linear and neural network system identification techniques;Allen;Physiological measurement,1999

4. Age-related changes in peripheral pulse timing characteristics at the ears, fingers and toes;Allen;Journal of human hypertension,2002

5. Deep speech 2: End-to-end speech recognition in english and mandarin;Amodei,2016

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2. Design and validation of dual-point time-differentiated photoplethysmogram (2PPG) wearable for cuffless blood pressure estimation;Computer Methods and Programs in Biomedicine;2024-08

3. Non-Contact Blood Pressure Estimation From Radar Signals by a Stacked Deformable Convolution Network;IEEE Journal of Biomedical and Health Informatics;2024-08

4. Reconstruction of arterial blood pressure waveforms based on squeeze-and-excitation network models using electrocardiography and photoplethysmography signals;Knowledge-Based Systems;2024-07

5. Prediction of arterial blood pressure waveforms based on Multi-Task learning;Biomedical Signal Processing and Control;2024-06

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