mlsanityData to 7 Oct 2026

TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise

arXiv 1409.5181 ↗First posted 18 Sep 2014cs.CYcited by 40

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Abstract (arXiv)

Heart rate monitoring using wrist-type photoplethysmographic (PPG) signals during subjects' intensive exercise is a difficult problem, since the signals are contaminated by extremely strong motion artifacts caused by subjects' hand movements. So far few works have studied this problem. In this work, a general framework, termed TROIKA, is proposed, which consists of signal decomposiTion for denoising, sparse signal RecOnstructIon for high-resolution spectrum estimation, and spectral peaK trAcking with verification. The TROIKA framework has high estimation accuracy and is robust to strong motion artifacts. Many variants can be straightforwardly derived from this framework. Experimental results on datasets recorded from 12 subjects during fast running at the peak speed of 15 km/hour showed that the average absolute error of heart rate estimation was 2.34 beat per minute (BPM), and the Pearson correlation between the estimates and the ground-truth of heart rate was 0.992. This framework is of great values to wearable devices such as smart-watches which use PPG signals to monitor heart rate for fitness.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Sep 2014.

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Citing papers per year: 2021: 4; 2022: 7; 2023: 12; 2024: 5; 2025: 8; 2026: 4.

40 papers.

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  1. 2021Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advancescited by 54
  2. 2023Deep Imputation of Missing Values in Time Series Health Data: A Review with Benchmarkingcited by 29
  3. 2023Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learningcited by 18
  4. 2022Q-PPG: Energy-Efficient PPG-based Heart Rate Monitoring on Wearable Devicescited by 14
  5. 2024WildPPG: A Real-World PPG Dataset of Long Continuous Recordingscited by 14
  6. 2025GPT-PPG: A GPT-based Foundation Model for Photoplethysmography Signalscited by 12
  7. 2022Embedding Temporal Convolutional Networks for Energy-Efficient PPG-Based Heart Rate Monitoringcited by 8
  8. 2023BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief Propagationcited by 8
  9. 2024KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatchcited by 7
  10. 2025PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detectioncited by 7
  11. 2022Robust and Energy-efficient PPG-based Heart-Rate Monitoringcited by 6
  12. 2022Self-Supervised PPG Representation Learning Shows High Inter-Subject Variabilitycited by 6
28 more
  1. 2023Sparse learned kernels for interpretable and efficient medical time series processingcited by 6
  2. 2024An Unsupervised Approach for Periodic Source Detection in Time Seriescited by 5
  3. 2025Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learningcited by 5
  4. 2023Tiny-PPG: A Lightweight Deep Neural Network for Real-Time Detection of Motion Artifacts in Photoplethysmogram Signals on Edge Devicescited by 4
  5. 2023TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcarecited by 3
  6. 2022Multi-Head Cross-Attentional PPG and Motion Signal Fusion for Heart Rate Estimationcited by 2
  7. 2023A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearablescited by 2
  8. 2024Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learningcited by 2
  9. 2024SensorBench: Benchmarking LLMs in Coding-Based Sensor Processingcited by 2
  10. 2026A General Framework for Generative Self-supervised Learning in Non-invasive Estimation of Physiological Parameters Using Photoplethysmographycited by 2
  11. 2021Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced Errorcited by 1
  12. 2023PPG-based Heart Rate Estimation with Efficient Sensor Sampling and Learning Modelscited by 1
  13. 2023Multi-Scale and Multi-Modal Contrastive Learning Network for Biomedical Time Seriescited by 1
  14. 2025Temporal Cardiovascular Dynamics for Improved PPG-Based Heart Rate Estimationcited by 1
  15. 2026Deriving Health Metrics from the Photoplethysmogram: Benchmarks and Insights from MIMIC-III-Ext-PPGcited by 1
  16. 2021Synthesizing Skeletal Motion and Physiological Signals as a Function of a Virtual Human's Actions and Emotionscited by 0
  17. 2021Motion Artifact Reduction In Photoplethysmography For Reliable Signal Selectioncited by 0
  18. 2022FastBVP-Net: a lightweight pulse extraction network for measuring heart rhythm via facial videoscited by 0
  19. 2022Exploring Interactions and Regulations in Collaborative Learning: An Interdisciplinary Multimodal Datasetcited by 0
  20. 2023Efficient and Direct Inference of Heart Rate Variability using Both Signal Processing and Machine Learningcited by 0
  21. 2023Energy-efficient Wearable-to-Mobile Offload of ML Inference for PPG-based Heart-Rate Estimationcited by 0
  22. 2023Grassroots Operator Search for Model Edge Adaptationcited by 0
  23. 2025Joint Attention Mechanism Learning to Facilitate Opto-physiological Monitoring during Physical Activitycited by 0
  24. 2025TAU: Modeling Temporal Consistency Through Temporal Attentive U-Net for PPG Peak Detectioncited by 0
  25. 2025Self-Supervised Autoencoder Network for Robust Heart Rate Extraction from Noisy Photoplethysmogram: Applying Blind Source Separation to Biosignal Analysiscited by 0
  26. 2025Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projectionscited by 0
  27. 2026Multi-site PPG: An In-the-Wild Physiological Dataset from Emerging Multi-site Wearablescited by 0
  28. 2026Physically-Constrained Harmonic Separation for Robust Heart and Respiratory Rate Estimation from Wrist Photoplethysmographycited by 0