Non-invasive glucose estimation leaderboard

PPG Signals for Blood Glucose Measurement (Kermani / Mendeley): MARD

Name: Kermani / Mendeley MARD leaderboard: non-invasive glucose estimation
Creator: ChatPPG

9 reported results for non-invasive glucose estimation on PPG Signals for Blood Glucose Measurement (Kermani / Mendeley), ranked by MARD. Top reported: PLS…

This page ranks every result ChatPPG has recorded for non-invasive glucose estimation on PPG Signals for Blood Glucose Measurement (Kermani / Mendeley), measured by MARD (%) (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: PPG Signals for Blood Glucose Measurement (Kermani / Mendeley), MARD (%). Reported rankings; evaluation protocols may differ.
Rank	Method & evaluation	MARD (%)↓ Lower is better
1	PLS (Islam) PPG features + partial least squares (Islam et al. 2021 method) [reproduction] Evaluation details Trained on all VitalDB data, tested on the 67 MUST (Kermani) recordings (Supraja et al. 2026 out-of-distribution test). MUST glucose spans only 88-183 mg/dL, so mean prediction scores well; R² was below zero for every model. Reported as of: 2026-10-16	10.67
2	MFCC + XGBoost (Prabha) MFCC features + XGBoost (Prabha et al. 2022 method) [reproduction] Evaluation details Trained on all VitalDB data, tested on the 67 MUST (Kermani) recordings (Supraja et al. 2026 out-of-distribution test). MUST glucose spans only 88-183 mg/dL, so mean prediction scores well; R² was below zero for every model. Reported as of: 2026-10-16	11.69
3	ResNet34-1s ResNet34, 1 s segments (Zeynali et al. 2025) Evaluation details Original paper: trained on VitalDB (random 70/15/15 split), external test on the MUST (Kermani) dataset with 1 s peak-centred segments resampled to 100 Hz (Tables 6-7). Reported as of: 2026-10-16	12.8
4	CNN-LSTM-Att-1s CNN-LSTM-Attention, 1 s segments (Zeynali et al. 2025) Evaluation details Original paper: trained on VitalDB (random 70/15/15 split), external test on the MUST (Kermani) dataset with 1 s peak-centred segments resampled to 100 Hz (Tables 6-7). Reported as of: 2026-10-16	13
5	Mean baseline Mean-of-training-set baseline [reproduction] Evaluation details Trained on all VitalDB data, tested on the 67 MUST (Kermani) recordings (Supraja et al. 2026 out-of-distribution test). MUST glucose spans only 88-183 mg/dL, so mean prediction scores well; R² was below zero for every model. Reported as of: 2026-10-16	14.13
6	XGBoost (Gupta) PPG features + XGBoost (Gupta et al. 2021 method) [reproduction] Evaluation details Trained on all VitalDB data, tested on the 67 MUST (Kermani) recordings (Supraja et al. 2026 out-of-distribution test). MUST glucose spans only 88-183 mg/dL, so mean prediction scores well; R² was below zero for every model. Reported as of: 2026-10-16	14.46
7	ResNet34 (Zeynali) ResNet34 on raw 1 s PPG (Zeynali et al. 2025 method) [reproduction] Evaluation details Trained on all VitalDB data, tested on the 67 MUST (Kermani) recordings (Supraja et al. 2026 out-of-distribution test). MUST glucose spans only 88-183 mg/dL, so mean prediction scores well; R² was below zero for every model. Reported as of: 2026-10-16	14.99
8	VGG16-1s VGG16, 1 s segments (Zeynali et al. 2025) Evaluation details Original paper: trained on VitalDB (random 70/15/15 split), external test on the MUST (Kermani) dataset with 1 s peak-centred segments resampled to 100 Hz (Tables 6-7). Reported as of: 2026-10-16	15
9	1D-CNN (Alghlayini) 1D-CNN on raw PPG (Alghlayini et al. 2023 method) [reproduction] Evaluation details Trained on all VitalDB data, tested on the 67 MUST (Kermani) recordings (Supraja et al. 2026 out-of-distribution test). MUST glucose spans only 88-183 mg/dL, so mean prediction scores well; R² was below zero for every model. Reported as of: 2026-10-16	16.56

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

PPG Signals for Blood Glucose Measurement (Kermani / Mendeley)

Subjects: 23
Signals: ppg
Licence: CC BY 4.0

Related leaderboards

Other metrics on PPG Signals for Blood Glucose Measurement (Kermani / Mendeley)

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). Kermani / Mendeley MARD leaderboard: non-invasive glucose estimation [Data set]. ChatPPG Research Hub. https://chatppg.com/research/leaderboards/glucose-estimation/ppg-bgl-kermani-mard-pct

BibTeX

@misc{chatppg_glucose_estimation_ppg_bgl_kermani_mard_pct,
  author       = {{ChatPPG}},
  title        = {{Kermani / Mendeley MARD leaderboard: non-invasive glucose estimation}},
  year         = {2026},
  month        = oct,
  howpublished = {\url{https://chatppg.com/research/leaderboards/glucose-estimation/ppg-bgl-kermani-mard-pct}},
  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: "Kermani / Mendeley MARD leaderboard: non-invasive glucose estimation"
authors:
  - name: "ChatPPG"
url: "https://chatppg.com/research/leaderboards/glucose-estimation/ppg-bgl-kermani-mard-pct"
date-released: "2026-10-16"