Device research record
RespiBAN chest band
Signals and sensors
From the device record. Fields the source does not state are left out.
- Maker
- BiosignalsPlux / RespiBAN-class
- Form factor
- Chest
- Signals recorded
- ECG, Respiration, Temperature, Accelerometer
- Also called
- RespiBAN, RespiBAN (chest), chest RespiBAN-class (ECG/resp/temp)
Datasets recorded with this device
Leaderboards on its datasets
Benchmarks computed on data recorded with RespiBAN chest band.
- Heart rate estimation: PPG-DaLiA, (1 result)
- Heart rate estimation: PPG-DaLiA, Mean absolute HR error (BPM) (11 results)
- Heart rate estimation: WESAD, Mean absolute HR error (BPM) (2 results)
- Mental workload / stress: WESAD, Accuracy (2 results)
- Mental workload / stress: WESAD, Area under ROC (7 results)
- Mental workload / stress: WESAD, (1 result)
Models trained or evaluated on its data
Models whose published training or evaluation datasets include recordings from this device.
- AnyPPG (2026)
- CAP (2026)
- CardioState-JEPA (2026)
- DNA-PPG (2026)
- ECG-PPG JEPA (Bridging ECG and PPG; unnamed in paper) (2026)
- Geenjaar multimodal-supervision PPG FM (2026)
- GPT-PPG (2025)
- HiPPT (2026)
- MSMA-PPG (2027)
- NormWear-2 (2026)
- PaPaGei-S (2025)
- ProtoMM (Pulse-Motion) (2025)
Show 8 more
- Pulse-PPG (2025)
- PulseLM (2026)
- RAE-PPG (2026)
- SLIP (Sensor Language-Informed Pretraining; any-channel sensor-language FM) (2026)
- SOTER (2026)
- TEX-MEX (2026)
- TF-MambaNet (2026)
- VitalAgent (2026)
Papers using these datasets
- AnyPPG: An ECG-Guided PPG Foundation Model Trained on Over 100,000 Hours of Recordings for Holistic Health Profiling
- BeatFlow-ECG: Rectified Flow for ECG Reconstruction from Indirect Wearable Signals
- Calibrated photoplethysmography-derived heart rate variability approximates electrocardiographic gold-standard performance for stress-state classification
- CAP: Towards PPG Universal Representation Learning with Patient-level Supervision
- Source-Learned Reliance for Selective Test-Time Adaptation of Multimodal Time Series (CARAT)
- CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation
- Cross-Modal Correlation Fusion for End-to-End ECG–PPG Stress Classification
- DNA-PPG: A Foundation Model for Photoplethysmography via Dual Neighborhood Alignment
- Bridging ECG and PPG: Latent-Space Prediction for Robust Physiological Analysis
- A robust PPG foundation model using multimodal physiological supervision
- GPT-PPG: a GPT-based foundation model for photoplethysmography signals
- HiPPT: Physiology-Grounded Wearable PPG Representation Learning via Multi-Scope Text Alignment
Show 15 more
- MSMA-PPG: Channel-Aligned Expert Routing for Selected-Wavelength PPG Prediction
- Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics
- PPG-Bench: A Unified Benchmark for PPG Foundation Models
- ProtoMM: Shared Prototypes for a Multimodal Pulse-Motion Foundation Model
- Pulse-PPG: An Open-Source Field-Trained PPG Foundation Model for Wearable Applications Across Lab and Field Settings
- pulselm-ppg-text-qa-2026
- Quality-Aware Wrist Photoplethysmography for Subject Independent Stress-State Monitoring: ECG-Referenced Validation and Selective Prediction
- RAE-PPG: Duration-Grounded Retain-and-Extend Pretraining for PPG Foundation Models
- Reliability-Evidence Fusion for Selective Heart-Rate Estimation from Wearable PPG: A Transformation-Aware Cross-Cohort Study
- ReliaGate: Reliability Routing for Low-Stakes Wearable Stress Prediction
- Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection
- SLIP: Learning Transferable Sensor Models via Language-Informed Pretraining
- TF-MambaNet: A Temporal and Frequency Fused Bidirectional Mamba Architecture for PPG Foundation Model
- Wrist PPG Stress Classification on WESAD: Interval Features Compared with Beat-Shape and Wavelet Features
- VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data