Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 18, 2025Hypertension

Abstract TH121: Evaluating the Performance of AI-Driven photoplethysmography(PPG) Models for Cuffless Blood Pressure Monitoring: A Meta-Analysis

View Full Paper
Ask AI
Bookmark
Share

Authors

PAParth AdrejiyaVSVedant ShahVPViraj Panchal

Discussion

Loading...

Member takes

Overview

Meta-analysis compares AI-based PPG models' accuracy with traditional blood pressure measurement techniques.

Key Points

  • The PPG-based blood pressure model provides a mean absolute error of 3.052 mmHg for diastolic pressure.
  • The pooled mean difference for systolic blood pressure was reported at 1.277 mmHg, suggesting slight overestimation.
  • This meta-analysis encompassed data from 15 studies with 20,562 patients evaluating accuracy of cuffless monitoring.
  • Findings support the use of photoplethysmography for improved diastolic blood pressure estimation under AAMI standards.

Cite This Study

Adrejiya et al. (2025) studied this question.

synapsesocial.com/papers/68f3b2fb3f213c1f8b4d34e5https://doi.org/10.1161/hyp.82.suppl_1.th121
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Method-Centric and Structured Review of Artificial Intelligence-Based Cuffless Blood Pressure Estimation Using ECG and PPG2026
  2. 2Practical Optimization of Deep Learning Models for Cuffless Blood Pressure Estimation From Photoplethysmography2026
  3. 3New photoplethysmogram indicators for improving cuffless and continuous blood pressure estimation accuracy2018 · 79 citations
  4. 4The Recent Advancements to Measure the Blood Pressure Using Photoplethysmography, Electrocardiogram, and Microchannel2025
  5. 5A continuous cuffless blood pressure measurement from optimal PPG characteristic features using machine learning algorithms2024 · 14 citations