<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Wearable Consent on Formize.com Blog</title><link>https://blog.formize.com/tags/wearable-consent/</link><description>Recent content in Wearable Consent on Formize.com Blog</description><generator>Hugo</generator><language>en</language><atom:link href="https://blog.formize.com/tags/wearable-consent/index.xml" rel="self" type="application/rss+xml"/><item><title>Accelerating Wearable Health Data Consent Management with Formize</title><link>https://blog.formize.com/accelerating-wearable-health-data-consent-management-with-fo/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://blog.formize.com/accelerating-wearable-health-data-consent-management-with-fo/</guid><description>&lt;h1 id="accelerating-wearable-health-data-consent-management-with-formize">Accelerating Wearable Health Data Consent Management with Formize&lt;/h1>
&lt;p>Wearable devices generate a constant stream of biometric data—heart rate, sleep patterns, activity levels, glucose readings, and more. While the clinical and commercial value of this data is undeniable, regulatory frameworks such as &lt;a href="https://gdpr.eu/" target="_blank" rel="noreferrer nofollow">GDPR&lt;/a>, &lt;a href="https://www.hhs.gov/hipaa/index.html" target="_blank" rel="noreferrer nofollow">HIPAA&lt;/a>, and the California Consumer Privacy Act demand explicit, revocable, and auditable consent from each user. Traditional consent workflows, built on static PDFs or email threads, quickly become bottlenecks, especially when devices are deployed at scale.&lt;/p></description></item></channel></rss>