<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0">
  <channel>
    <title>OPUS 4 Latest Documents RSS Feed</title>
    <description>Latest documents</description>
    <link>http://publikationen.ub.uni-frankfurt.de/index/index/</link>
    <pubDate>Sun, 20 Sep 2009 17:04:59 +0200</pubDate>
    <lastBuildDate>Sun, 20 Sep 2009 17:04:59 +0200</lastBuildDate>
    <item>
      <title>EEG processing with TESPAR for depth of anesthesia detection</title>
      <link>http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/7075</link>
      <description>Poster presentation: Introduction Adequate anesthesia is crucial to the success of surgical interventions and subsequent recovery. Neuroscientists, surgeons, and engineers have sought to understand the impact of anesthetics on the information processing in the brain and to properly assess the level of anesthesia in an non-invasive manner. Studies have indicated a more reliable depth of anesthesia (DOA) detection if multiple parameters are employed. Indeed, commercial DOA monitors (BIS, Narcotrend, M-Entropy and A-line ARX) use more than one feature extraction method. Here, we propose TESPAR (Time Encoded Signal Processing And Recognition) a time domain signal processing technique novel to EEG DOA assessment that could enhance existing monitoring devices. ...</description>
      <author>Vasile V. Moca; Bertram Scheller; Raul C. Mureşan; Michael Daunderer; Gordon Pipa</author>
      <category>article</category>
      <guid>http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/7075</guid>
      <pubDate>Sun, 20 Sep 2009 17:04:59 +0200</pubDate>
    </item>
  </channel>
</rss>
