<?xml-stylesheet type="text/xsl" href="https://community.element14.com/cfs-file/__key/system/syndication/rss.xsl" media="screen"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:wfw="http://wellformedweb.org/CommentAPI/"><channel><title>Skier impact monitor 09 - PSoC4 performance measurements</title><link>/challenges-projects/design-challenges/sudden-impact/b/blog/posts/skier-impact-monitor-09---psoc4-performance-measurements</link><description>( Complete list of all blog entries in this series )Maybe you followed what I did write so far. If this is so, you might remember by article about the head injury criterion . There I explained how the car industry determines how severe a head impact is</description><dc:language>en-US</dc:language><generator>Telligent Community 12</generator><item><title>RE: Skier impact monitor 09 - PSoC4 performance measurements</title><link>https://community.element14.com/challenges-projects/design-challenges/sudden-impact/b/blog/posts/skier-impact-monitor-09---psoc4-performance-measurements</link><pubDate>Fri, 20 Feb 2015 19:54:25 GMT</pubDate><guid isPermaLink="false">93d5dcb4-84c2-446f-b2cb-99731719e767:98a22177-2688-4e02-bbd5-18d7885cdbb1</guid><dc:creator>DAB</dc:creator><slash:comments>0</slash:comments><description>&lt;p&gt;You might want to do a precalc check on the data to see if any one axis exceeds the limit.&lt;/p&gt;&lt;p&gt;You can do a parametric analysis to see what combinations of axis data enters into the critical area where you need to do the detailed calculation.&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;Set up a matrix based upon a integer input level and use fuzzy logic to determine if the change is light, moderate, or severe.&lt;/p&gt;&lt;p&gt;Then use a simple logic table that would require two of the three axes to be severe to be qualified as a potential problem.&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;Just a thought,&lt;/p&gt;&lt;p&gt;DAB&lt;/p&gt;&lt;img src="https://community.element14.com/aggbug?PostID=19971&amp;AppID=108&amp;AppType=Weblog&amp;ContentType=0" width="1" height="1"&gt;</description></item><item><title>RE: Skier impact monitor 09 - PSoC4 performance measurements</title><link>https://community.element14.com/challenges-projects/design-challenges/sudden-impact/b/blog/posts/skier-impact-monitor-09---psoc4-performance-measurements</link><pubDate>Fri, 20 Feb 2015 01:55:49 GMT</pubDate><guid isPermaLink="false">93d5dcb4-84c2-446f-b2cb-99731719e767:98a22177-2688-4e02-bbd5-18d7885cdbb1</guid><dc:creator>clem57</dc:creator><slash:comments>1</slash:comments><description>&lt;p&gt;I have a simple suggestion: A table of precompute squares like this:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;9/81&lt;/li&gt;&lt;li&gt;20/400&lt;/li&gt;&lt;li&gt;30/900&lt;/li&gt;&lt;/ol&gt;&lt;p&gt;The table can be used to get an approximation like this: if you had 500, you know if is 500 is closer to 20/400 and farther from 30/900 = 22 ish making a linear assumption. (480 actually!) &lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;Clem&lt;/p&gt;&lt;img src="https://community.element14.com/aggbug?PostID=19971&amp;AppID=108&amp;AppType=Weblog&amp;ContentType=0" width="1" height="1"&gt;</description></item></channel></rss>