---
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.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
- **Dataset Questions**: schugh1@umbc.edu
- **Technical Issues**: zhasan3@umbc.edu
---
*Dataset Version: 1.0*