mlsanityData to 14 Oct 2026

PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation

arXiv 2509.19215 ↗First posted 23 Sep 2025cs.LGcited by 6

On the map: Knowledge distillation → Distillation for medical imaging

Abstract (arXiv)

Photoplethysmography (PPG) is widely used in wearable health monitoring, yet large PPG foundation models remain difficult to deploy on resource-limited devices. We present PPG-Distill, a knowledge distillation framework that transfers both global and local knowledge through prediction-, feature-, and patch-level distillation. PPG-Distill incorporates morphology distillation to preserve local waveform patterns and rhythm distillation to capture inter-patch temporal structures. On heart rate estimation and atrial fibrillation detection, PPG-Distill improves student performance by up to 21.8% while achieving 7X faster inference and reducing memory usage by 19X, enabling efficient PPG analysis on wearables.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Placed in Distillation for medical imaging, one of 12 directions in Knowledge distillation. Builds on 18 of its 40 references that are in the map. First posted on arXiv 23 Sep 2025.

Builds on

18 of 40 references.

References · 18

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,324
  3. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  4. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 2,039
  5. 2014FitNets: Hints for Thin Deep Netscited by 1,653
  6. 2020Knowledge Distillation: A Surveycited by 1,603
  7. 2019Relational Knowledge Distillationcited by 889
  8. 2023Large-scale Training of Foundation Models for Wearable Biosignalscited by 95
  9. 2024PaPaGei: Open Foundation Models for Optical Physiological Signalscited by 69
  10. 2023LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended Versioncited by 50
  11. 2025Pulse-PPG: An Open-Source Field-Trained PPG Foundation Model for Wearable Applications Across Lab and Field Settingscited by 37
  12. 2025Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictionscited by 18
6 more
  1. 2025Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networkscited by 14
  2. 2025TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillationcited by 12
  3. 2025Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series?cited by 6
  4. 2025U-Cast: Learning Hierarchical Structures for High-Dimensional Time Series Forecastingcited by 5
  5. 2025Pre-training Epidemic Time Series Forecasters with Compartmental Prototypescited by 3
  6. 2025SeizureFormer: A Transformer Model for IEA-Based Seizure Risk Forecastingcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 3.

6 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025Towards Characterizing Knowledge Distillation of PPG Heart Rate Estimation Models
  2. 2026PPG-LM: A Photoplethysmography-Language Model with Multi-Level Clinical Alignment
  3. 2024Wearable Accelerometer Foundation Models for Health via Knowledge Distillation
  4. 2025Robust Photoplethysmography Signal Denoising via Mamba Networks
  5. 2025PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detection
  6. 2023PPG-to-ECG Signal Translation for Continuous Atrial Fibrillation Detection via Attention-based Deep State-Space Modeling
  7. 2026P2E-VQ: ECG-linked representation augmentation for PPG via discrete patch retrieval
  8. 2022Q-PPG: Energy-Efficient PPG-based Heart Rate Monitoring on Wearable Devices