Non-invasive glucose estimation leaderboard

VitalDB: MAE (mg/dL)

Name: VitalDB MAE (mg/dL) leaderboard: non-invasive glucose estimation
Creator: ChatPPG

6 reported results for non-invasive glucose estimation on VitalDB, ranked by MAE (mg/dL). Top reported: MFCC + XGBoost (Prabha) (25.42). Every row cites its…

This page ranks every result ChatPPG has recorded for non-invasive glucose estimation on VitalDB, measured by Glucose MAE (mg/dL) (lower is better). Each number is copied from the publication cited in its row, and ranks apply only within this dataset and metric.

Glucose estimation: VitalDB, Glucose MAE (mg/dL). Reported rankings; evaluation protocols may differ.
Rank	Method & evaluation	Glucose MAE (mg/dL)↓ Lower is better
1	MFCC + XGBoost (Prabha) MFCC features + XGBoost (Prabha et al. 2022 method) Evaluation details Reproduced by Supraja et al. 2026 on VitalDB intraoperative finger PPG vs lab glucose; leave-some-participants-out (test = 1/5 of participants, non-overlapping), mean of 5 folds. A predict-the-training-mean baseline scores within ~1 mg/dL of every model. Reported as of: 2026-10-16	25.42
2	XGBoost (Gupta) PPG features + XGBoost (Gupta et al. 2021 method) Evaluation details Reproduced by Supraja et al. 2026 on VitalDB intraoperative finger PPG vs lab glucose; leave-some-participants-out (test = 1/5 of participants, non-overlapping), mean of 5 folds. A predict-the-training-mean baseline scores within ~1 mg/dL of every model. Reported as of: 2026-10-16	25.77
3	ResNet34 (Zeynali) ResNet34 on raw 1 s PPG (Zeynali et al. 2025 method) Evaluation details Reproduced by Supraja et al. 2026 on VitalDB intraoperative finger PPG vs lab glucose; leave-some-participants-out (test = 1/5 of participants, non-overlapping), mean of 5 folds. A predict-the-training-mean baseline scores within ~1 mg/dL of every model. Reported as of: 2026-10-16	25.93
4	1D-CNN (Alghlayini) 1D-CNN on raw PPG (Alghlayini et al. 2023 method) Evaluation details Reproduced by Supraja et al. 2026 on VitalDB intraoperative finger PPG vs lab glucose; leave-some-participants-out (test = 1/5 of participants, non-overlapping), mean of 5 folds. A predict-the-training-mean baseline scores within ~1 mg/dL of every model. Reported as of: 2026-10-16	26.05
5	PLS (Islam) PPG features + partial least squares (Islam et al. 2021 method) Evaluation details Reproduced by Supraja et al. 2026 on VitalDB intraoperative finger PPG vs lab glucose; leave-some-participants-out (test = 1/5 of participants, non-overlapping), mean of 5 folds. A predict-the-training-mean baseline scores within ~1 mg/dL of every model. Reported as of: 2026-10-16	26.14
6	Mean baseline Mean-of-training-set baseline Evaluation details Reproduced by Supraja et al. 2026 on VitalDB intraoperative finger PPG vs lab glucose; leave-some-participants-out (test = 1/5 of participants, non-overlapping), mean of 5 folds. A predict-the-training-mean baseline scores within ~1 mg/dL of every model. Reported as of: 2026-10-16	26.39

Rows are ranked only within this task × dataset × metric. Protocols can differ; read each method's evaluation details before comparing. Latest reported row: 2026-10-16.

About the dataset

VitalDB: intraoperative multi-parameter vitals (PhysioNet mirror)

Subjects: 6388
Signals: ppg, ecg, resp, abp, co2
Licence: CC BY 4.0 (PhysioNet release)

Related leaderboards

Other metrics on VitalDB

Non-invasive glucose estimation on other datasets

Data and submissions

Download every leaderboard as JSON or CSV. Missing a published result? Email hello@chatppg.com with the paper link and the exact table it comes from.

Cite this

Cite the page URL and the date you accessed it. Please also cite the original publications listed above.

APA

ChatPPG. (2026). VitalDB MAE (mg/dL) leaderboard: non-invasive glucose estimation [Data set]. ChatPPG Research Hub. https://chatppg.com/research/leaderboards/glucose-estimation/vitaldb-mae-mgdl

BibTeX

@misc{chatppg_glucose_estimation_vitaldb_mae_mgdl,
  author       = {{ChatPPG}},
  title        = {{VitalDB MAE (mg/dL) leaderboard: non-invasive glucose estimation}},
  year         = {2026},
  month        = oct,
  howpublished = {\url{https://chatppg.com/research/leaderboards/glucose-estimation/vitaldb-mae-mgdl}},
  note         = {ChatPPG Research Hub}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this resource, please cite it as below."
type: dataset
title: "VitalDB MAE (mg/dL) leaderboard: non-invasive glucose estimation"
authors:
  - name: "ChatPPG"
url: "https://chatppg.com/research/leaderboards/glucose-estimation/vitaldb-mae-mgdl"
date-released: "2026-10-16"