<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sleep Staging | CV_YIMING_ZHONG</title><link>https://pandarua220.github.io/CV/tags/sleep-staging/</link><atom:link href="https://pandarua220.github.io/CV/tags/sleep-staging/index.xml" rel="self" type="application/rss+xml"/><description>Sleep Staging</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sat, 01 Feb 2025 00:00:00 +0000</lastBuildDate><image><url>https://pandarua220.github.io/CV/media/icon_hu7729264130191091259.png</url><title>Sleep Staging</title><link>https://pandarua220.github.io/CV/tags/sleep-staging/</link></image><item><title>Contactless Smart Infant Sleep Monitoring System</title><link>https://pandarua220.github.io/CV/project/sleep/</link><pubDate>Sat, 01 Feb 2025 00:00:00 +0000</pubDate><guid>https://pandarua220.github.io/CV/project/sleep/</guid><description>&lt;p>Developed a multispectral physiological imaging system for precise, contactless monitoring of infant vital signs, in collaboration with a leading hospital in Wenzhou.&lt;/p>
&lt;p>Established an interpretable video-based sleep/wake classification model to enhance monitoring accuracy from consumer-grade to clinical-grade standards.&lt;/p>
&lt;p>Leveraged ECG and PPG signals to extract and validate infant motion metrics for preliminary sleep analysis.&lt;/p>
&lt;p>Deployed open-source human pose estimation and optical flow algorithms to compute key-point motion features, confirming feasibility of camera-based polysomnography (PSG) for infant sleep staging.&lt;/p>
&lt;p>Conducted camera-based PSG monitoring on 100 infants to establish normative sleep-stage benchmarks.&lt;/p>
&lt;p>Extracted limb movement coordination and intensity features from video data, applying SVM and Random Forest classifiers for binary and multi-class sleep-stage classification.&lt;/p>
&lt;p>Applied DL algorithms (LSTM, Transformer) to improve the accuracy of infant sleep stage classification.&lt;/p></description></item></channel></rss>