<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T03:56:23Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/113157" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/113157</identifier><datestamp>2026-06-06T00:54:44Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Sepandar Kamvar.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Koren, Gal, M. Eng. Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-01-12T21:00:33Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2018-01-12T21:00:33Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/113157</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1018308103</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student-submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 79-80).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Wearable sensors have been used in research efforts aiming to develop a mapping between physiological responses of the autonomic nervous system, namely electrodermal activity and heart rate variability, to emotional reactions such as arousal, stress, and attention. While many studies conducted with existing sensors have focused primarily on adults, some have recently begun utilizing them to characterize cognitive and social processes in children. As research in early childhood development continues, a physiological sensor tailored for data acquisition in early education environments, where children spend much of their time socializing and learning, will prove especially valuable for advancing further studies in the field. In this thesis, I present the design and implementation of a compact and lightweight wristband monitor for children, that unobtrusively tracks a set of vital signs that are known to demonstrate sympathetic and parasympathetic responses in the general population. The finalized system is evaluated for data quality and ease of analysis by applying signal processing methods on data collected over a two-week period at a Montessori preschool, where children continuously wore the device each day while engaging in various lesson activities and social interactions.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Gal Koren.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">80 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Senti : a wearable sensor for physiological data acquisition in early education</dim:field>
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   	&lt;Title>Senti : a wearable sensor for physiological data acquisition in early education&lt;/Title>
   	&lt;Subtitle>Wearable sensor for physiological data acquisition in early education&lt;/Subtitle>
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   	&lt;PublicationDate>2016&lt;/PublicationDate>
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   	&lt;Abstract>Wearable sensors have been used in research efforts aiming to develop a mapping between physiological responses of the autonomic nervous system, namely electrodermal activity and heart rate variability, to emotional reactions such as arousal, stress, and attention. While many studies conducted with existing sensors have focused primarily on adults, some have recently begun utilizing them to characterize cognitive and social processes in children. As research in early childhood development continues, a physiological sensor tailored for data acquisition in early education environments, where children spend much of their time socializing and learning, will prove especially valuable for advancing further studies in the field. In this thesis, I present the design and implementation of a compact and lightweight wristband monitor for children, that unobtrusively tracks a set of vital signs that are known to demonstrate sympathetic and parasympathetic responses in the general population. The finalized system is evaluated for data quality and ease of analysis by applying signal processing methods on data collected over a two-week period at a Montessori preschool, where children continuously wore the device each day while engaging in various lesson activities and social interactions.&lt;/Abstract>
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