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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>About | MEDWEAR</title>
<link rel="stylesheet" href="style.css" />
<link rel="icon" href="favicon.svg" type="image/svg+xml" />
</head>
<body>
<header>
<a href="index.html" class="header-brand">MEDWEAR</a>
<nav>
<a href="index.html">Home</a>
<a href="about.html" class="active">About</a>
<a href="documentation.html">Documentation</a>
<a href="schemas.html">Schemas</a>
<a href="med-api.html">MED-API</a>
<a href="use-cases.html">Use Cases</a>
<a href="contribute.html">Contribute</a>
</nav>
</header>
<div class="page-banner" style="background-image: url('assets/images/hero-about.jpg')">
<div class="page-banner-content">
<h1>About MEDWEAR</h1>
<p>Community-driven standards for wearable health data</p>
</div>
</div>
<div class="content-container">
<main>
<section>
<h2>About the Project</h2>
<p>
Wearable devices are rapidly transforming healthcare by enabling continuous, real-time monitoring
of patients outside clinical settings. MEDWEAR is a community-driven initiative funded by ETH Zurich's
Open Research Data initiative to create open standards for structuring and exchanging high-frequency
data from medical wearables.
</p>
<p>
We address the fragmentation of the digital health ecosystem by building on existing standards -
Open mHealth, HL7 FHIR, IEEE 11073, and openEHR - to define lightweight, extensible schemas
suitable for modern sensing devices and middleware systems like ROS 2 and MQTT.
</p>
</section>
<section>
<h2>Why Standardization Matters</h2>
<p>
Although wearable technologies have become integral to modern healthcare - supporting use cases
from chronic disease management to preventive care - the lack of common data formats hinders
integration with EHRs, AI systems, and clinical decision tools. Over 80% of healthcare data
remains unstructured and difficult to reuse.
</p>
<p>
Standardizing wearable data supports interoperability, clinical utility, patient safety, and
research reproducibility. MEDWEAR provides schemas and APIs that support high-frequency data,
real-time streaming, and device-agnostic modeling.
</p>
<h3>Key challenges addressed</h3>
<ul>
<li>Fragmented systems with incompatible data formats</li>
<li>Lack of EHR integration</li>
<li>Data privacy and regulatory constraints</li>
<li>Barriers to real-time, high-frequency data streaming</li>
<li>Limited clinical adoption and ROI evidence</li>
</ul>
</section>
<section>
<h2>Standards & Design Principles</h2>
<p>
MEDWEAR schemas follow the
<a href="https://standards.ieee.org/standard/1752-2021.html" target="_blank" rel="noopener">IEEE 1752-2021
Standard</a>
and are compatible with the <a href="http://www.openmhealth.org" target="_blank" rel="noopener">Open
mHealth</a>
framework, extending both to support high-frequency raw sensor streams.
</p>
<ul>
<li><strong>Vendor-agnostic</strong> - no dependency on proprietary device formats.</li>
<li><strong>FAIR</strong> - Findable, Accessible, Interoperable, and Reusable.</li>
<li><strong>Modular</strong> - signal schemas are self-contained and composable.</li>
<li><strong>Middleware-ready</strong> - definitions ship as both JSON Schemas and ROS 2 <code>.msg</code>
files.</li>
<li><strong>Extensible</strong> - new signal types can be added without breaking existing consumers.</li>
</ul>
<h3>Relationship to existing standards</h3>
<table>
<thead>
<tr>
<th>Standard</th>
<th>Scope</th>
<th>MEDWEAR relationship</th>
</tr>
</thead>
<tbody>
<tr>
<td><a href="http://www.openmhealth.org" target="_blank" rel="noopener">Open mHealth</a></td>
<td>Structured JSON schemas for health data</td>
<td>Base schema format; MEDWEAR extends it for raw, high-frequency signals</td>
</tr>
<tr>
<td><a href="https://standards.ieee.org/ieee/1752.1/6982/" target="_blank" rel="noopener">IEEE
1752.1-2021</a></td>
<td>Mobile health data quality and interoperability</td>
<td>Normative reference for schema design and quality requirements</td>
</tr>
<tr>
<td><a href="https://www.hl7.org/fhir/" target="_blank" rel="noopener">HL7 FHIR</a></td>
<td>Clinical data exchange (EHR integration)</td>
<td>Target interoperability layer for clinical deployment</td>
</tr>
<tr>
<td><a href="https://www.openehr.org/" target="_blank" rel="noopener">openEHR</a></td>
<td>Semantic clinical models</td>
<td>Reference for clinical semantic precision</td>
</tr>
<tr>
<td><a href="https://sagroups.ieee.org/11073/phd-wg/" target="_blank" rel="noopener">IEEE 11073-PHD</a>
</td>
<td>Personal health device communication</td>
<td>Informs device-level metadata modeling</td>
</tr>
</tbody>
</table>
</section>
<section>
<h2>Collaborating Institutions</h2>
<ul>
<li>ETH Zurich - Open Research Data Initiative</li>
<li>SCAI Lab, ETH Zurich</li>
<li>DART Lab, Lake Lucerne Institute</li>
<li>University of Zurich (UZH)</li>
<li>SUPSI</li>
</ul>
</section>
</main>
</div>
<footer>
<div class="footer-logos">
<img src="assets/images/scai_logo.png" alt="SCAI Lab Logo" />
<img src="assets/images/ethz_logo.png" alt="ETH Zurich Logo" class="ethz-logo" />
</div>
<p>© 2026 ETH Zurich – MEDWEAR Project | Contact: diego.paez@scai.ethz.ch · monica.perezserrano@hest.ethz.ch</p>
</footer>
</body>
</html>