MEDWEAR

Usage Examples

Using MEDWEAR JSON Schemas

The schemas define the data structure for wearable sensor data. You can validate your data against these schemas to ensure interoperability.

Example: ECG Data JSON

{
  "schema_id": "org.medwear.biosignal.ecg",
  "version": "1.0",
  "data": {
    "ecg": [0.12, 0.15, 0.11, ...],
    "sample_rate": 250,
    "units": "mV"
  },
  "metadata": {
    "device_id": "device1234",
    "timestamp": "2025-06-30T15:30:00Z"
  }
}

Loading MEDWEAR Schemas in Python

import json
from jsonschema import validate

with open('ecg_schema.json') as schema_file:
    schema = json.load(schema_file)

with open('ecg_data.json') as data_file:
    data = json.load(data_file)

validate(instance=data, schema=schema)
print("Data is valid according to MEDWEAR ECG schema.")

Further Resources

• JSON Schema documentation
• MEDWEAR GitHub Repository
• Explore MEDWEAR Schemas (new page)

Documentation & Resources

📚 User Guides

• Using MEDWEAR Data Schemas
• ROS 2 Integration Guide
• Data Conversion Workflow

📄 JSON Schemas

Our schemas extend Open mHealth to include raw sensor formats.
View all schemas on a dedicated page | View on GitHub

🤖 ROS 2 Messages

Download ROS 2 `.msg` definitions for integration with healthcare robots and assistive devices.
View ROS 2 message package

🔁 Conversion Tools

Command-line tools and notebooks to convert CSV/JSON/wearable data to MEDWEAR-compliant format.
Explore conversion tools

📊 Example Datasets

Sample anonymized datasets for development and testing.
Download examples

🧠 Publications

• "MEDWEAR: Data Standardization of Wearable Devices for Healthcare Applications" (in preparation)
• Symposium [PDF]

🛠️ Contribute

Found a bug or want to add support for new sensors?
See our contributing guide.

❓ FAQs

Coming soon: Frequently asked questions about MEDWEAR schemas and implementation.