README.md

---
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"
---



<div align="center">
  <h1 style="font-size: 4em; margin-bottom: 0.2em;">MPSC-RR Dataset</h1>
  <h2 style="font-size: 2.5em; margin-top: 0; color: #666;">Respiratory Waveform Reconstruction using Persistent Independent Particles Tracking from Video</h2>
</div>



<p align="center">
  <a href="https://huggingface.co/datasets/justchugh/MPSC-RR">
    <img src="https://img.shields.io/badge/Dataset-HuggingFace-yellow?style=for-the-badge" alt="Dataset">
  </a>
  &nbsp;&nbsp;
  <a href="https://justchugh.github.io/RRPIPs.github.io/#paper">
    <img src="https://img.shields.io/badge/Paper-CHASE%202025-blue?style=for-the-badge" alt="Paper">
  </a>
  &nbsp;&nbsp;
  <a href="https://github.com/mxahan/RRPIPS">
    <img src="https://img.shields.io/badge/Code-GitHub-black?style=for-the-badge" alt="Code">
  </a>
  &nbsp;&nbsp;
  <a href="https://justchugh.github.io/RRPIPs.github.io/">
    <img src="https://img.shields.io/badge/Website-GitHub-red?style=for-the-badge" alt="Website">
  </a>
  &nbsp;&nbsp;
  <a href="LICENSE">
    <img src="https://img.shields.io/badge/License-CC%20BY%204.0-green?style=for-the-badge" alt="License">
  </a>
</p>


[![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**: [email protected]
- **Dataset Questions**: [email protected]

## Team

<div align="center">

<table border="0" style="border: none;">
  <tr>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://mxahan.github.io/digital-cv/">
        <img src="assets/authors/Zahid.png" width="180px;" style="border-radius: 50%;" alt="Zahid Hasan"/><br />
        <sub><b>Zahid Hasan</b></sub>
      </a>
    </td>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://mahmed10.github.io/personalwebpage/">
        <img src="assets/authors/Masud.png" width="180px;" style="border-radius: 50%;" alt="Masud Ahmed"/><br />
        <sub><b>Masud Ahmed</b></sub>
      </a>
    </td>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://www.linkedin.com/in/shadman-sakib15/">
        <img src="assets/authors/Shadman.png" width="180px;" style="border-radius: 50%;" alt="Shadman Sakib"/><br />
        <sub><b>Shadman Sakib</b></sub>
      </a>
    </td>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://justchugh.github.io">
        <img src="assets/authors/Snehalraj.png" width="180px;" style="border-radius: 50%;" alt="Snehalraj Chugh"/><br />
        <sub><b>Snehalraj Chugh</b></sub>
      </a>
    </td>
  </tr>
</table>

<table border="0" style="border: none;">
  <tr>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://www.linkedin.com/in/azim-khan-10/">
        <img src="assets/authors/Azim.png" width="180px;" style="border-radius: 50%;" alt="Md Azim Khan"/><br />
        <sub><b>Md Azim Khan</b></sub>
      </a>
    </td>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://azmfaridee.github.io">
        <img src="assets/authors/Zaher.png" width="180px;" style="border-radius: 50%;" alt="Abu Zaher MD Faridee"/><br />
        <sub><b>Abu Zaher MD Faridee</b></sub>
      </a>
    </td>
    <td align="center" style="border: none; padding: 20px;">
      <a href="https://mpsc.umbc.edu/nroy">
        <img src="assets/authors/Nirmalya.png" width="180px;" style="border-radius: 50%;" alt="Nirmalya Roy"/><br />
        <sub><b>Nirmalya Roy</b></sub>
      </a>
    </td>
  </tr>
</table>

</div>
---

*Dataset Version: 1.0*