📄 node3.html

📁 Input/Data Acquisition System Design for Human Computer Interfacing
💻 HTML
字号:
<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML 2.2//EN"><!--Converted with LaTeX2HTML 96.1 (Feb 5, 1996) by Nikos Drakos (nikos@cbl.leeds.ac.uk), CBLU, University of Leeds --><HTML><HEAD><TITLE>2.1 The Sensor </TITLE><META NAME="description" CONTENT="2.1 The Sensor "><META NAME="keywords" CONTENT="sensors"><META NAME="resource-type" CONTENT="document"><META NAME="distribution" CONTENT="global"><LINK REL=STYLESHEET HREF="sensors.css" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/sensors.css"></HEAD><BODY BGCOLOR="#FFFFFF" TEXT="#000000" LANG="EN"> <A NAME="tex2html110" HREF="node4.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node4.html"><IMG WIDTH=37 HEIGHT=24 ALIGN=BOTTOM ALT="next" SRC="next_motif.gif" tppabs="http://ccrma.stanford.edu/Images//next_motif.gif"></A> <A NAME="tex2html108" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html"><IMG WIDTH=26 HEIGHT=24 ALIGN=BOTTOM ALT="up" SRC="up_motif.gif" tppabs="http://ccrma.stanford.edu/Images//up_motif.gif"></A> <A NAME="tex2html102" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html"><IMG WIDTH=63 HEIGHT=24 ALIGN=BOTTOM ALT="previous" SRC="previous_motif.gif" tppabs="http://ccrma.stanford.edu/Images//previous_motif.gif"></A>   <BR><B> Next:</B> <A NAME="tex2html111" HREF="node4.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node4.html">2.2 Signal Conditioning </A><B>Up:</B> <A NAME="tex2html109" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html">2 General Overview  </A><B> Previous:</B> <A NAME="tex2html103" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html">2 General Overview  </A><BR> <P><H2><A NAME="SECTION00021000000000000000">2.1 The Sensor </A></H2><P>One approach to choosing an appropriate sensor would be to model computer sensing after 
the five human senses: gustatory (taste), olfactory (smell), tactile, auditory, and visual. The better approach, however, is to decide what volitional (or even non-volitional) actions of the user will be 
important for the particular computer application. In other words, it is important to decide what gestures by the human are appropriate for the application and determine what sensor is optimal in 
measuring that gesture. Before determining what computer inputs to use we must determine what human outputs are appropriate.  
For example, say we would like to use the tension in the forearm as a way of telling the computer to pick up a virtual (or real) coffee cup.  We would then incorporate into our HCI  a sensor that could 
pick up the electrical signal from the muscle of the forearm (this will be discussed in section 3.4 below). If we had patterned computer senses solely after human senses, this would not be possible.<P>Sensors can be categorized in many ways. They can be categorized by the underlying physics of their operation.  However, one physical principle can be used to measure many different phenomena. For example, 
the piezoelectric effect can measure force, flexure, acceleration, heat, and acoustic vibrations.  Sensors can be categorized by the particular phenomenon they measure. However, one phenomenon can be 
measured by many physical principles.  For example, sound waves can be measured by the piezoelectric effect, capacitance, electromagnetic field effects, and changes in resistance.  Sensors can also be 
grouped by a particular application.  For example, one could group all sensors together that can be used to measure distance.  However, since there is a clever way to use almost any sensor to measure 
distance, this is not necessarily a good way to analyze sensors either.<P>With no method of categorization being clearly superior to any other, the authors arbitrarily chose to discuss sensors according to their underlying physical principles.  Section 3 will give an overview 
of many different sensors, the physical properties by which they operate, and the actions that they measure. In reading this section, keep in mind what is the sensitivity of the sensor, what inaccuracies 
could occur in using it to sense gestures, and what are the properties of the signal that will be generated by the sensor (e.g., temporal structure, spectrum, statistics, and dynamic range).<P><HR><A NAME="tex2html110" HREF="node4.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node4.html"><IMG WIDTH=37 HEIGHT=24 ALIGN=BOTTOM ALT="next" SRC="next_motif.gif" tppabs="http://ccrma.stanford.edu/Images//next_motif.gif"></A> <A NAME="tex2html108" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html"><IMG WIDTH=26 HEIGHT=24 ALIGN=BOTTOM ALT="up" SRC="up_motif.gif" tppabs="http://ccrma.stanford.edu/Images//up_motif.gif"></A> <A NAME="tex2html102" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html"><IMG WIDTH=63 HEIGHT=24 ALIGN=BOTTOM ALT="previous" SRC="previous_motif.gif" tppabs="http://ccrma.stanford.edu/Images//previous_motif.gif"></A>   <BR><B> Next:</B> <A NAME="tex2html111" HREF="node4.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node4.html">2.2 Signal Conditioning </A><B>Up:</B> <A NAME="tex2html109" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html">2 General Overview  </A><B> Previous:</B> <A NAME="tex2html103" HREF="node2.html" tppabs="http://ccrma.stanford.edu/CCRMA/Courses/252/sensors/node2.html">2 General Overview  </A><P><ADDRESS><I>Tim Stilson <BR>Thu Oct 17 16:32:33 PDT 1996</I></ADDRESS></BODY></HTML>
⌨️ 快捷键说明

复制代码 Ctrl + C
搜索代码 Ctrl + F
全屏模式 F11
切换主题 Ctrl + Shift + D
显示快捷键 ?
增大字号 Ctrl + =
减小字号 Ctrl + -