<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/77c12c61e54e44958f05d8aa402c6906&quot; frameborder=&quot;0&quot; width=&quot;1152&quot; height=&quot;864&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>864</height><width>1152</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>864</thumbnail_height><thumbnail_width>1152</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/77c12c61e54e44958f05d8aa402c6906-61984289e70e2220.gif</thumbnail_url><duration>362.813</duration><title>MODULE 2 - 5: Kramers-Kronig (KK) Testing</title><description>In this video, I demonstrate how to use the KK test to validate data collected from the Pulsenics dashboard&apos;s analytics page. We navigate to the validation tab, select our Nyquist plot, and explore options like M selection and robust KK tests to ensure a good fit. I highlight that a root mean squared error below 1% indicates a valid EIS measurement, confirming that our system is in a steady state and responding linearly. I also show how to specify frequency ranges to refine our fit. Please review the results and consider adjusting circuit elements if necessary.</description></oembed>