ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2005.03357
  4. Cited By
Estimating Blood Pressure from Photoplethysmogram Signal and Demographic
  Features using Machine Learning Techniques

Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques

7 May 2020
M. H. Chowdhury
Md Nazmul Islam Shuzan
M. Chowdhury
Z. Mahbub
Mohammad Monir Uddin
Amith Khandakar
M. Reaz
ArXiv (abs)PDFHTML

Papers citing "Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques"

13 / 13 papers shown
Cuffless Blood Pressure Estimation from Six Wearable Sensor Modalities in Multi-Motion-State Scenarios
Cuffless Blood Pressure Estimation from Six Wearable Sensor Modalities in Multi-Motion-State Scenarios
Yiqiao Chen
Fazheng Xu
Zijian Huang
Juchi He
Zhenghui Feng
79
0
0
01 Dec 2025
Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals
Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals
Saurabh Kataria
Yi Wu
Zhaoliang Chen
Hyunjung Gloria Kwak
Yuhao Xu
...
C. Jabaley
Tim Buchman
Sivasubramanium V Bhavani
Randall J Lee
Xiao Hu
AI4TSAI4MHLM&MA
225
0
0
16 Oct 2025
GPT-PPG: A GPT-based Foundation Model for Photoplethysmography Signals
GPT-PPG: A GPT-based Foundation Model for Photoplethysmography SignalsPhysiological Measurement (PM), 2025
Zhaoliang Chen
C. Ding
Saurabh Kataria
Runze Yan
Minxiao Wang
Randall J Lee
Xiao Hu
LM&MAMedIm
352
17
0
11 Mar 2025
A Review of Deep Learning Methods for Photoplethysmography Data
A Review of Deep Learning Methods for Photoplethysmography Data
Guangkun Nie
Jiabao Zhu
Gongzheng Tang
Deyun Zhang
Shijia Geng
Qinghao Zhao
Shenda Hong
319
25
0
23 Jan 2024
Machine Learning-Based Diabetes Detection Using Photoplethysmography
  Signal Features
Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features
Filipe A. C. Oliveira
F. M. Dias
Marcelo A. F. Toledo
D. Cárdenas
Douglas A. Almeida
Estela Ribeiro
J. Krieger
Marco A. Gutierrez
109
6
0
02 Aug 2023
PPG Signals for Hypertension Diagnosis: A Novel Method using Deep
  Learning Models
PPG Signals for Hypertension Diagnosis: A Novel Method using Deep Learning Models
G. Frederick
T. Yaswant
A. BrinthaTherese
219
4
0
14 Apr 2023
ReViSe: Remote Vital Signs Measurement Using Smartphone Camera
ReViSe: Remote Vital Signs Measurement Using Smartphone CameraIEEE Access (IEEE Access), 2022
Donghao Qiao
Amtul Haq Ayesha
F. Zulkernine
Raihan Masroor
Nauman Jaffar
CVBM
277
38
0
13 Jun 2022
A machine learning-based severity prediction tool for diabetic
  sensorimotor polyneuropathy using Michigan neuropathy screening
  instrumentations
A machine learning-based severity prediction tool for diabetic sensorimotor polyneuropathy using Michigan neuropathy screening instrumentations
Fahmida Haque
M. Reaz
M. E. Chowdhury
R. Malik
Mohammed Alhatou
S. Kobashi
I. Ara
S. Ali
A. Bakar
Geetika Srivastava
193
2
0
28 Mar 2022
SleepPPG-Net: a deep learning algorithm for robust sleep staging from
  continuous photoplethysmography
SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmographyIEEE journal of biomedical and health informatics (IEEE JBHI), 2022
Kevin Kotzen
Peter H. Charlton
Sharon Salabi
Lea Amar
A. Landesberg
Joachim A. Behar
259
55
0
11 Feb 2022
A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP)
  from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals
A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) SignalsItalian National Conference on Sensors (INS), 2021
S. Mahmud
Nabil Ibtehaz
Amith Khandakar
Anas Tahir
Tawsifur Rahman
K. R. Islam
Md. Shafayet Hossain
M. S. Rahman
Mohammad Tariqul Islam
M. Chowdhury
183
71
0
12 Nov 2021
A Machine Learning Model for Early Detection of Diabetic Foot using
  Thermogram Images
A Machine Learning Model for Early Detection of Diabetic Foot using Thermogram Images
Amith Khandakar
M. Chowdhury
M. Reaz
S. Ali
Md. Anwarul Hasan
S. Kiranyaz
Tawsifur Rahman
R. Alfkey
A. Bakar
R. Malik
226
127
0
27 Jun 2021
A Novel Non-Invasive Estimation of Respiration Rate from
  Photoplethysmograph Signal Using Machine Learning Model
A Novel Non-Invasive Estimation of Respiration Rate from Photoplethysmograph Signal Using Machine Learning Model
Md Nazmul Islam Shuzan
M. H. Chowdhury
M. Chowdhury
Mohammad Monir Uddin
Amith Khandakar
Z. Mahbub
N. Nawaz
96
2
0
18 Feb 2021
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning,
  Segmentation and Visualization
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and VisualizationIEEE Access (IEEE Access), 2020
Tawsifur Rahman
Amith Khandakar
M. A. Kadir
K. R. Islam
Khandaker F. Islam
...
Tahir Hamid
M. Islam
Z. Mahbub
M. Ayari
M. Chowdhury
261
497
0
29 Jul 2020
1
Page 1 of 1