--- viewer: false dataset_info: features: - name: video dtype: image - name: video_id dtype: string - name: subject_id dtype: int64 - name: view_position dtype: string splits: - name: train num_bytes: 5575000000 num_examples: 31 download_size: 5575000000 dataset_size: 5575000000 license: cc-by-4.0 task_categories: - video-classification - image-classification tags: - respiratory-monitoring - healthcare - computer-vision configs: - config_name: default default: true dataset_card: README.md pretty_name: "MPSC-RR: Multi-Position Respiratory Monitoring Dataset" ---

MPSC-RR Dataset

Respiratory Waveform Reconstruction using Persistent Independent Particles Tracking from Video

[![Dataset Overview](dataset.mp4)](dataset.mp4) # Dataset Description The MPSC-RR dataset is a comprehensive collection of RGB videos designed for contactless respiratory rate estimation and respiratory waveform reconstruction research. The dataset captures respiratory-induced movements across multiple body positions and camera angles, providing diverse scenarios for developing robust respiratory monitoring algorithms. ### Key Features - **Multi-Position Coverage**: Front, back, side, and lying positions - **Natural Breathing Patterns**: Regular, slow, and fast breathing captured - **Diverse Demographics**: Adult volunteers across different age groups and backgrounds - **Ground Truth Annotations**: Vernier Go Direct Respiration Belt measurements - **High-Quality Videos**: RGB videos with clear respiratory motion visibility - **Real-World Conditions**: Varied lighting, clothing, and environmental settings ## Dataset Statistics - **Total Videos**: 31 video sessions - **Subjects**: 24 adult volunteers (Subject IDs: 1-24) - **Duration**: 2.5-5 minutes per video (Average: ~4 minutes) - **Resolution**: Varied resolutions from 304×304 to 1602×1080 - **Frame Rate**: Primarily 30 FPS (with some at 30.1, 29, and 24 FPS) - **Total Duration**: ~2.1 hours of respiratory monitoring data - **Total Size**: 5.18 GB ## Data Structure ### Video Files ``` s{subject_id}_{view_position}.{ext} ``` **Naming Convention:** - `s1_front.mov` - Subject 1, front view - `s20_side.mp4` - Subject 20, side view (Note: one video in MP4 format) - `s24_lying.mov` - Subject 24, lying position **View Positions:** - `front` - Frontal chest/abdomen view (6 videos) - `back` - Back/shoulder movement view (4 videos) - `side` - Side profile view (16 videos) - `lying` - Lying down position (5 videos) ### Metadata Structure ```python { "video_id": str, # e.g., "s1_front" "subject_id": int, # Subject identifier (1-24) "view_position": str, # front, back, side, lying "duration_seconds": float, # Video duration "resolution": str, # e.g., "1920x1080" "frame_rate": float, # 30.0, 30.1, 29.0, or 24.0 FPS "file_size_mb": float, # File size in megabytes "filename": str # Actual filename with extension } ``` ## Usage ### Loading the Dataset ```python from datasets import load_dataset # Load all videos dataset = load_dataset("justchugh/MPSC-RR") # Access video information sample = dataset[0] video_id = sample["video_id"] subject_id = sample["subject_id"] view_position = sample["view_position"] ``` ### Filtering Videos ```python # Get front view videos front_videos = dataset.filter(lambda x: x["view_position"] == "front") # Get specific subject's videos subject_1 = dataset.filter(lambda x: x["subject_id"] == 1) # Get lying position videos lying_videos = dataset.filter(lambda x: x["view_position"] == "lying") ``` ### Basic Analysis ```python # Count videos per position positions = [sample["view_position"] for sample in dataset] position_counts = {pos: positions.count(pos) for pos in set(positions)} print("Videos per position:", position_counts) # List all subjects subjects = set(sample["subject_id"] for sample in dataset) print(f"Subjects: {sorted(subjects)}") ``` ### Data Collection ### Equipment - **Camera**: Standard RGB cameras (mobile phones, mounted cameras) - **Ground Truth**: Vernier Go Direct Respiration Belt for pressure measurements - **Distance**: 1-1.5 meters from subjects - **Environment**: Clinical laboratory setting with controlled conditions ### Protocol 1. **Subject Preparation**: Comfortable positioning with clear view of respiratory regions 2. **Baseline Recording**: 30-second calibration period 3. **Data Collection**: 3-5 minutes of natural breathing 4. **Ground Truth Sync**: Synchronized pressure belt data collection 5. **Quality Check**: Manual verification of respiratory cycles ### View Positions Explained | Position | Description | Captured Regions | Use Case | Count | | --------- | --------------- | ------------------------ | ------------------------------- | ----- | | `front` | Frontal view | Chest, abdomen expansion | Standard respiratory monitoring | 6 | | `back` | Back view | Shoulder, back movement | Posterior respiratory motion | 4 | | `side` | Side profile | Chest wall movement | Lateral respiratory dynamics | 16 | | `lying` | Supine position | Abdomen, chest (lying) | Sleep/rest respiratory patterns | 5 | ## Dataset Distribution | Subject Range | Video Count | Positions Available | | ------------- | ----------- | ------------------- | | 1-2 | 6 videos | front, back, lying | | 3 | 2 videos | back, lying | | 4 | 1 video | front | | 5 | 2 videos | front, lying | | 6 | 1 video | front | | 7-22 | 16 videos | side (primarily) | | 23 | 1 video | front | | 24 | 2 videos | back, lying | ## Benchmark Results Performance of state-of-the-art methods on MPSC-RR: | Method | MAE (bpm) | RMSE (bpm) | Modality | | ---------------- | -------------- | -------------- | -------- | | Intensity-based | 3.25 | 5.12 | RGB | | Optical Flow | 2.42 | 3.89 | RGB | | PIPs++ | 1.62 | 2.92 | RGB | | **RRPIPS** | **1.01** | **1.80** | RGB | ## Applications This dataset supports research in: - **Contactless Vital Sign Monitoring** - **Multi-Position Respiratory Analysis** - **Computer Vision for Healthcare** - **Sleep and Rest Monitoring** - **Wearable-Free Health Tracking** - **Clinical Decision Support Systems** ## Data Quality ### Inclusion Criteria - Clear visibility of respiratory-induced motion - Stable video recording (minimal camera movement) - Synchronized ground truth data available - Adequate lighting conditions ### Quality Metrics - **Motion Clarity**: All videos show visible respiratory movement - **Synchronization**: <50ms offset between video and pressure data - **Duration**: Minimum 148 seconds per recording - **Resolution**: Varied resolutions optimized for respiratory motion capture ## Related Datasets - **AIR-125**: Infant respiratory monitoring (125 videos, infants) - **BIDMC**: PPG and respiration signals (53 recordings, clinical) - **Sleep Database**: NIR/IR respiratory data (28 videos, adults) ## Ethical Considerations - **IRB Approval**: All data collection approved by institutional review board - **Informed Consent**: Written consent obtained from all participants - **Privacy Protection**: Faces blurred or cropped when necessary - **Data Anonymization**: No personally identifiable information included - **Voluntary Participation**: Participants could withdraw at any time ## Citation If you use this dataset in your research, please cite: ```bibtex @inproceedings{hasan2025rrpips, title={RRPIPS: Respiratory Waveform Reconstruction using Persistent Independent Particles Tracking from Video}, author={Hasan, Zahid and Ahmed, Masud and Sakib, Shadman and Chugh, Snehalraj and Khan, Md Azim and Faridee, Abu Zaher MD and Roy, Nirmalya}, booktitle={ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)}, year={2025}, pages={1--12}, doi={10.1145/3721201.3721366} } ``` ## Quick Start ```python # Install required packages pip install datasets # Load and explore dataset from datasets import load_dataset dataset = load_dataset("justchugh/MPSC-RR") print(f"Total videos: {len(dataset)}") print(f"First video: {dataset[0]['video_id']}") print(f"Positions available: {set(s['view_position'] for s in dataset)}") # Example: Get all side view videos side_videos = dataset.filter(lambda x: x["view_position"] == "side") print(f"Side view videos: {len(side_videos)}") ``` ## License This dataset is released under [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). ## Links - **Code Repository**: https://github.com/mxahan/RRPIPS - **Website Repository**: https://github.com/justchugh/RRPIPs.github.io ## Contact - **Technical Issues**: zhasan3@umbc.edu - **Dataset Questions**: schugh1@umbc.edu ## Team

_{Zahid Hasan}

_{Masud Ahmed}

_{Shadman Sakib}

_{Snehalraj Chugh}

_{Md Azim Khan}

_{Abu Zaher MD Faridee}

_{Nirmalya Roy}

--- *Dataset Version: 1.0*