ArticleFrontiers in physiology2026
Feasibility of heart rate monitoring in hemodialysis patients using visible imaging: a pilot study.
Article in Frontiers in physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Continuous vital signal monitoring is essential for patients undergoing hemodialysis sessions in which physiological instability, body fatigue, and cardiovascular complications may occur and require early medical interventions. However, conventional contactbased sensors such as electrocardiogram (ECG) have several limitations due to increased skin sensitivity, skin irritation, and interference with clinical procedures. Objective: This study proposes a remote photoplethysmography (rPPG) framework for continuous heart rate monitoring of stage-5 chronic kidney disease (CKD-5) patients. Methods: A pilot cohort of eight patients diagnosed with stage-5 chronic kidney disease undergoing hemodialysis sessions were monitored using synchronized RGB video and ECG reference measurements to generate 32 hours of video data. The proposed framework incorporates an automated facial landmark tracking and a dual-masking-based skin detection approach to robustly define regions-of-interest (ROI). A multimethod ensemble fusion is integrated through spectral analysis, peak detection, and harmonic product spectrum analysis for confidence-weighted final heart rate estimation. Results: The proposed framework achieved a mean absolute error (MAE) of 1.16 beats per minute (BPM) and root mean squared error (RMSE) of 1.86 BPM with a mean bias error of -0.68 BPM among all patients irrespective of lower visibility due to mask and partial occlusion. Conclusion: These findings suggest that noncontact heart rate monitoring of patients diagnosed with advanced renal diseases is feasible using visible imaging and the rPPG method. By addressing clinical variability, the proposed framework suggests the potential of remote heart rate monitoring in a controlled dialysis-unit environment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.