<?xml version="1.0" encoding="UTF-8" ?>
<oai_dc:dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>A comparative study of in-air trajectories at short and long distances in online handwriting</dc:title>
<dc:creator>Alonso-Martinez, Carlos</dc:creator>
<dc:creator>Faundez-Zanuy, Marcos</dc:creator>
<dc:creator>Mekyska, Jiri</dc:creator>
<dc:subject>Handwriting</dc:subject>
<dc:subject>Biometrics</dc:subject>
<dc:subject>In-air trajectories</dc:subject>
<dc:description>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</dc:description>
<dc:description>info:eu-repo/semantics/publishedVersion</dc:description>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2017</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</dc:identifier>
<dc:identifier>1866-9964</dc:identifier>
<dc:identifier>http://hdl.handle.net/20.500.12367/2529</dc:identifier>
<dc:identifier>10.1007/s12559-017-9501-5</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Cognitive Computation. 2017;9:712–720</dc:relation>
<dc:rights>(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</dc:rights>
<dc:rights>Attribution 4.0 International</dc:rights>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:format>9 p.</dc:format>
<dc:format>application/pdf</dc:format>
<dc:publisher>Springer Nature</dc:publisher>
</oai_dc:dc>
<?xml version="1.0" encoding="UTF-8" ?>
<d:DIDL schemaLocation="urn:mpeg:mpeg21:2002:02-DIDL-NS http://standards.iso.org/ittf/PubliclyAvailableStandards/MPEG-21_schema_files/did/didl.xsd">
<d:DIDLInfo>
<dcterms:created schemaLocation="http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/dcterms.xsd">2023-12-04T10:36:40Z</dcterms:created>
</d:DIDLInfo>
<d:Item id="hdl_20.500.12367_2529">
<d:Descriptor>
<d:Statement mimeType="application/xml; charset=utf-8">
<dii:Identifier schemaLocation="urn:mpeg:mpeg21:2002:01-DII-NS http://standards.iso.org/ittf/PubliclyAvailableStandards/MPEG-21_schema_files/dii/dii.xsd">urn:hdl:20.500.12367/2529</dii:Identifier>
</d:Statement>
</d:Descriptor>
<d:Descriptor>
<d:Statement mimeType="application/xml; charset=utf-8">
<oai_dc:dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>A comparative study of in-air trajectories at short and long distances in online handwriting</dc:title>
<dc:creator>Alonso-Martinez, Carlos</dc:creator>
<dc:creator>Faundez-Zanuy, Marcos</dc:creator>
<dc:creator>Mekyska, Jiri</dc:creator>
<dc:description>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</dc:description>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2017</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</dc:identifier>
<dc:identifier>1866-9964</dc:identifier>
<dc:identifier>http://hdl.handle.net/20.500.12367/2529</dc:identifier>
<dc:identifier>10.1007/s12559-017-9501-5</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Cognitive Computation. 2017;9:712–720</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</dc:rights>
<dc:rights>Attribution 4.0 International</dc:rights>
<dc:publisher>Springer Nature</dc:publisher>
</oai_dc:dc>
</d:Statement>
</d:Descriptor>
<d:Component id="20.500.12367_2529_1">
</d:Component>
</d:Item>
</d:DIDL>
<?xml version="1.0" encoding="UTF-8" ?>
<dim:dim schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
<dim:field authority="bab09de0-91a6-46fd-bf4f-5f51a361b1cf" confidence="600" element="contributor" mdschema="dc" qualifier="author">Alonso-Martinez, Carlos</dim:field>
<dim:field authority="bd6ec996-6f01-492f-9fdb-e2c4026d3d65" confidence="600" element="contributor" mdschema="dc" qualifier="author">Faundez-Zanuy, Marcos</dim:field>
<dim:field authority="34abaf20-0e22-488a-9415-a97f3dd5d3aa" confidence="600" element="contributor" mdschema="dc" qualifier="author">Mekyska, Jiri</dim:field>
<dim:field element="date" mdschema="dc" qualifier="accessioned">2023-12-04T10:36:40Z</dim:field>
<dim:field element="date" mdschema="dc" qualifier="available">2023-12-04T10:36:40Z</dim:field>
<dim:field element="date" mdschema="dc" qualifier="issued">2017</dim:field>
<dim:field element="identifier" lang="ca" mdschema="dc" qualifier="citation">Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</dim:field>
<dim:field element="identifier" lang="ca" mdschema="dc" qualifier="issn">1866-9964</dim:field>
<dim:field element="identifier" mdschema="dc" qualifier="uri">http://hdl.handle.net/20.500.12367/2529</dim:field>
<dim:field element="identifier" lang="ca" mdschema="dc" qualifier="doi">10.1007/s12559-017-9501-5</dim:field>
<dim:field element="description" lang="ca" mdschema="dc" qualifier="abstract">Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</dim:field>
<dim:field element="description" lang="ca" mdschema="dc" qualifier="version">info:eu-repo/semantics/publishedVersion</dim:field>
<dim:field element="format" lang="ca" mdschema="dc" qualifier="extent">9 p.</dim:field>
<dim:field element="language" lang="ca" mdschema="dc" qualifier="iso">eng</dim:field>
<dim:field element="publisher" lang="ca" mdschema="dc">Springer Nature</dim:field>
<dim:field element="relation" lang="ca" mdschema="dc" qualifier="ispartof">Cognitive Computation. 2017;9:712–720</dim:field>
<dim:field element="rights" lang="ca" mdschema="dc">(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</dim:field>
<dim:field element="rights" lang="*" mdschema="dc">Attribution 4.0 International</dim:field>
<dim:field element="rights" lang="*" mdschema="dc" qualifier="uri">http://creativecommons.org/licenses/by/4.0/</dim:field>
<dim:field element="rights" mdschema="dc" qualifier="accessLevel">info:eu-repo/semantics/openAccess</dim:field>
<dim:field element="subject" lang="ca" mdschema="dc" qualifier="other">Handwriting</dim:field>
<dim:field element="subject" lang="ca" mdschema="dc" qualifier="other">Biometrics</dim:field>
<dim:field element="subject" lang="ca" mdschema="dc" qualifier="other">In-air trajectories</dim:field>
<dim:field element="title" lang="ca" mdschema="dc">A comparative study of in-air trajectories at short and long distances in online handwriting</dim:field>
<dim:field element="type" lang="ca" mdschema="dc">info:eu-repo/semantics/article</dim:field>
<dim:field element="embargo" lang="ca" mdschema="dc" qualifier="terms">cap</dim:field>
</dim:dim>
<?xml version="1.0" encoding="UTF-8" ?>
<thesis schemaLocation="http://www.ndltd.org/standards/metadata/etdms/1.0/ http://www.ndltd.org/standards/metadata/etdms/1.0/etdms.xsd">
<title>A comparative study of in-air trajectories at short and long distances in online handwriting</title>
<creator>Alonso-Martinez, Carlos</creator>
<creator>Faundez-Zanuy, Marcos</creator>
<creator>Mekyska, Jiri</creator>
<description>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</description>
<date>2023-12-04</date>
<date>2023-12-04</date>
<date>2017</date>
<type>info:eu-repo/semantics/article</type>
<identifier>Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</identifier>
<identifier>1866-9964</identifier>
<identifier>http://hdl.handle.net/20.500.12367/2529</identifier>
<identifier>10.1007/s12559-017-9501-5</identifier>
<language>eng</language>
<relation>Cognitive Computation. 2017;9:712–720</relation>
<rights>http://creativecommons.org/licenses/by/4.0/</rights>
<rights>info:eu-repo/semantics/openAccess</rights>
<rights>(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</rights>
<rights>Attribution 4.0 International</rights>
<publisher>Springer Nature</publisher>
</thesis>
<?xml version="1.0" encoding="UTF-8" ?>
<record schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
<leader>00925njm 22002777a 4500</leader>
<datafield ind1=" " ind2=" " tag="042">
<subfield code="a">dc</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="720">
<subfield code="a">Alonso-Martinez, Carlos</subfield>
<subfield code="e">author</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="720">
<subfield code="a">Faundez-Zanuy, Marcos</subfield>
<subfield code="e">author</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="720">
<subfield code="a">Mekyska, Jiri</subfield>
<subfield code="e">author</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="260">
<subfield code="c">2017</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="520">
<subfield code="a">Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</subfield>
</datafield>
<datafield ind1="8" ind2=" " tag="024">
<subfield code="a">Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</subfield>
</datafield>
<datafield ind1="8" ind2=" " tag="024">
<subfield code="a">1866-9964</subfield>
</datafield>
<datafield ind1="8" ind2=" " tag="024">
<subfield code="a">http://hdl.handle.net/20.500.12367/2529</subfield>
</datafield>
<datafield ind1="8" ind2=" " tag="024">
<subfield code="a">10.1007/s12559-017-9501-5</subfield>
</datafield>
<datafield ind1="0" ind2="0" tag="245">
<subfield code="a">A comparative study of in-air trajectories at short and long distances in online handwriting</subfield>
</datafield>
</record>
<?xml version="1.0" encoding="UTF-8" ?>
<mets ID=" DSpace_ITEM_20.500.12367-2529" OBJID=" hdl:20.500.12367/2529" PROFILE="DSpace METS SIP Profile 1.0" TYPE="DSpace ITEM" schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd">
<metsHdr CREATEDATE="2024-09-03T17:59:35Z">
<agent ROLE="CUSTODIAN" TYPE="ORGANIZATION">
<name>TECNOCAMPUS</name>
</agent>
</metsHdr>
<dmdSec ID="DMD_20.500.12367_2529">
<mdWrap MDTYPE="MODS">
<xmlData schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:mods schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:name>
<mods:role>
<mods:roleTerm type="text">author</mods:roleTerm>
</mods:role>
<mods:namePart>Alonso-Martinez, Carlos</mods:namePart>
</mods:name>
<mods:name>
<mods:role>
<mods:roleTerm type="text">author</mods:roleTerm>
</mods:role>
<mods:namePart>Faundez-Zanuy, Marcos</mods:namePart>
</mods:name>
<mods:name>
<mods:role>
<mods:roleTerm type="text">author</mods:roleTerm>
</mods:role>
<mods:namePart>Mekyska, Jiri</mods:namePart>
</mods:name>
<mods:extension>
<mods:dateAccessioned encoding="iso8601">2023-12-04T10:36:40Z</mods:dateAccessioned>
</mods:extension>
<mods:extension>
<mods:dateAvailable encoding="iso8601">2023-12-04T10:36:40Z</mods:dateAvailable>
</mods:extension>
<mods:originInfo>
<mods:dateIssued encoding="iso8601">2017</mods:dateIssued>
</mods:originInfo>
<mods:identifier type="citation">Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</mods:identifier>
<mods:identifier type="issn">1866-9964</mods:identifier>
<mods:identifier type="uri">http://hdl.handle.net/20.500.12367/2529</mods:identifier>
<mods:identifier type="doi">10.1007/s12559-017-9501-5</mods:identifier>
<mods:abstract>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</mods:abstract>
<mods:language>
<mods:languageTerm authority="rfc3066">eng</mods:languageTerm>
</mods:language>
<mods:accessCondition type="useAndReproduction">(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018 Attribution 4.0 International</mods:accessCondition>
<mods:titleInfo>
<mods:title>A comparative study of in-air trajectories at short and long distances in online handwriting</mods:title>
</mods:titleInfo>
<mods:genre>info:eu-repo/semantics/article</mods:genre>
</mods:mods>
</xmlData>
</mdWrap>
</dmdSec>
<amdSec ID="FO_20.500.12367_2529_1">
<techMD ID="TECH_O_20.500.12367_2529_1">
<mdWrap MDTYPE="PREMIS">
<xmlData schemaLocation="http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd">
<premis:premis>
<premis:object>
<premis:objectIdentifier>
<premis:objectIdentifierType>URL</premis:objectIdentifierType>
<premis:objectIdentifierValue>https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/1/alonso_cogncomput_comp.pdf</premis:objectIdentifierValue>
</premis:objectIdentifier>
<premis:objectCategory>File</premis:objectCategory>
<premis:objectCharacteristics>
<premis:fixity>
<premis:messageDigestAlgorithm>MD5</premis:messageDigestAlgorithm>
<premis:messageDigest>2e48a5b719039d15adaa46b8b8251d75</premis:messageDigest>
</premis:fixity>
<premis:size>654669</premis:size>
<premis:format>
<premis:formatDesignation>
<premis:formatName>application/pdf</premis:formatName>
</premis:formatDesignation>
</premis:format>
</premis:objectCharacteristics>
<premis:originalName>alonso_cogncomput_comp.pdf</premis:originalName>
</premis:object>
</premis:premis>
</xmlData>
</mdWrap>
</techMD>
</amdSec>
<amdSec ID="FT_20.500.12367_2529_3">
<techMD ID="TECH_T_20.500.12367_2529_3">
<mdWrap MDTYPE="PREMIS">
<xmlData schemaLocation="http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd">
<premis:premis>
<premis:object>
<premis:objectIdentifier>
<premis:objectIdentifierType>URL</premis:objectIdentifierType>
<premis:objectIdentifierValue>https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/3/alonso_cogncomput_comp.pdf.txt</premis:objectIdentifierValue>
</premis:objectIdentifier>
<premis:objectCategory>File</premis:objectCategory>
<premis:objectCharacteristics>
<premis:fixity>
<premis:messageDigestAlgorithm>MD5</premis:messageDigestAlgorithm>
<premis:messageDigest>3dabc23fed1ac19f758c65c5455bbfc7</premis:messageDigest>
</premis:fixity>
<premis:size>29976</premis:size>
<premis:format>
<premis:formatDesignation>
<premis:formatName>text/plain</premis:formatName>
</premis:formatDesignation>
</premis:format>
</premis:objectCharacteristics>
<premis:originalName>alonso_cogncomput_comp.pdf.txt</premis:originalName>
</premis:object>
</premis:premis>
</xmlData>
</mdWrap>
</techMD>
</amdSec>
<fileSec>
<fileGrp USE="ORIGINAL">
<file ADMID="FO_20.500.12367_2529_1" CHECKSUM="2e48a5b719039d15adaa46b8b8251d75" CHECKSUMTYPE="MD5" GROUPID="GROUP_BITSTREAM_20.500.12367_2529_1" ID="BITSTREAM_ORIGINAL_20.500.12367_2529_1" MIMETYPE="application/pdf" SEQ="1" SIZE="654669">
</file>
</fileGrp>
<fileGrp USE="TEXT">
<file ADMID="FT_20.500.12367_2529_3" CHECKSUM="3dabc23fed1ac19f758c65c5455bbfc7" CHECKSUMTYPE="MD5" GROUPID="GROUP_BITSTREAM_20.500.12367_2529_3" ID="BITSTREAM_TEXT_20.500.12367_2529_3" MIMETYPE="text/plain" SEQ="3" SIZE="29976">
</file>
</fileGrp>
</fileSec>
<structMap LABEL="DSpace Object" TYPE="LOGICAL">
<div ADMID="DMD_20.500.12367_2529" TYPE="DSpace Object Contents">
<div TYPE="DSpace BITSTREAM">
</div>
</div>
</structMap>
</mets>
<?xml version="1.0" encoding="UTF-8" ?>
<mods:mods schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:name>
<mods:namePart>Alonso-Martinez, Carlos</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Faundez-Zanuy, Marcos</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Mekyska, Jiri</mods:namePart>
</mods:name>
<mods:extension>
<mods:dateAvailable encoding="iso8601">2023-12-04T10:36:40Z</mods:dateAvailable>
</mods:extension>
<mods:extension>
<mods:dateAccessioned encoding="iso8601">2023-12-04T10:36:40Z</mods:dateAccessioned>
</mods:extension>
<mods:originInfo>
<mods:dateIssued encoding="iso8601">2017</mods:dateIssued>
</mods:originInfo>
<mods:identifier type="citation">Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</mods:identifier>
<mods:identifier type="issn">1866-9964</mods:identifier>
<mods:identifier type="uri">http://hdl.handle.net/20.500.12367/2529</mods:identifier>
<mods:identifier type="doi">10.1007/s12559-017-9501-5</mods:identifier>
<mods:abstract>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</mods:abstract>
<mods:language>
<mods:languageTerm>eng</mods:languageTerm>
</mods:language>
<mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by/4.0/</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">Attribution 4.0 International</mods:accessCondition>
<mods:titleInfo>
<mods:title>A comparative study of in-air trajectories at short and long distances in online handwriting</mods:title>
</mods:titleInfo>
<mods:genre>info:eu-repo/semantics/article</mods:genre>
</mods:mods>
<?xml version="1.0" encoding="UTF-8" ?>
<oaire:record schemaLocation="http://namespaceopenaire.eu/schema/oaire/">
<dc:title>A comparative study of in-air trajectories at short and long distances in online handwriting</dc:title>
<datacite:creator>
<datacite:creatorName>Alonso-Martinez, Carlos</datacite:creatorName>
</datacite:creator>
<datacite:creator>
<datacite:creatorName>Faundez-Zanuy, Marcos</datacite:creatorName>
</datacite:creator>
<datacite:creator>
<datacite:creatorName>Mekyska, Jiri</datacite:creatorName>
</datacite:creator>
<dc:subject>Handwriting</dc:subject>
<dc:subject>Biometrics</dc:subject>
<dc:subject>In-air trajectories</dc:subject>
<dc:description>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</dc:description>
<dc:description>info:eu-repo/semantics/publishedVersion</dc:description>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2017</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<datacite:alternateIdentifier>Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</datacite:alternateIdentifier>
<datacite:alternateIdentifier>1866-9964</datacite:alternateIdentifier>
<datacite:alternateIdentifier>http://hdl.handle.net/20.500.12367/2529</datacite:alternateIdentifier>
<datacite:alternateIdentifier>10.1007/s12559-017-9501-5</datacite:alternateIdentifier>
<dc:language>eng</dc:language>
<dc:rights>(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</dc:rights>
<dc:rights>Attribution 4.0 International</dc:rights>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:format>9 p.</dc:format>
<dc:format>application/pdf</dc:format>
<dc:publisher>Springer Nature</dc:publisher>
<oaire:file>https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/1/alonso_cogncomput_comp.pdf</oaire:file>
</oaire:record>
<?xml version="1.0" encoding="UTF-8" ?>
<atom:entry schemaLocation="http://www.w3.org/2005/Atom http://www.kbcafe.com/rss/atom.xsd.xml">
<atom:id>http://hdl.handle.net/20.500.12367/2529/ore.xml</atom:id>
<atom:published>2023-12-04T10:36:40Z</atom:published>
<atom:updated>2023-12-04T10:36:40Z</atom:updated>
<atom:source>
<atom:generator>TECNOCAMPUS</atom:generator>
</atom:source>
<atom:title>A comparative study of in-air trajectories at short and long distances in online handwriting</atom:title>
<atom:author>
<atom:name>Alonso-Martinez, Carlos</atom:name>
</atom:author>
<atom:author>
<atom:name>Faundez-Zanuy, Marcos</atom:name>
</atom:author>
<atom:author>
<atom:name>Mekyska, Jiri</atom:name>
</atom:author>
<oreatom:triples>
<rdf:Description about="http://hdl.handle.net/20.500.12367/2529/ore.xml#atom">
<dcterms:modified>2023-12-04T10:36:40Z</dcterms:modified>
</rdf:Description>
<rdf:Description about="https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/1/alonso_cogncomput_comp.pdf">
<dcterms:description>ORIGINAL</dcterms:description>
</rdf:Description>
<rdf:Description about="https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/2/license_rdf">
<dcterms:description>CC-LICENSE</dcterms:description>
</rdf:Description>
<rdf:Description about="https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/3/alonso_cogncomput_comp.pdf.txt">
<dcterms:description>TEXT</dcterms:description>
</rdf:Description>
</oreatom:triples>
</atom:entry>
<?xml version="1.0" encoding="UTF-8" ?>
<qdc:qualifieddc schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
<dc:title>A comparative study of in-air trajectories at short and long distances in online handwriting</dc:title>
<dc:creator>Alonso-Martinez, Carlos</dc:creator>
<dc:creator>Faundez-Zanuy, Marcos</dc:creator>
<dc:creator>Mekyska, Jiri</dc:creator>
<dcterms:abstract>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</dcterms:abstract>
<dcterms:dateAccepted>2023-12-04T10:36:40Z</dcterms:dateAccepted>
<dcterms:available>2023-12-04T10:36:40Z</dcterms:available>
<dcterms:created>2023-12-04T10:36:40Z</dcterms:created>
<dcterms:issued>2017</dcterms:issued>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</dc:identifier>
<dc:identifier>1866-9964</dc:identifier>
<dc:identifier>http://hdl.handle.net/20.500.12367/2529</dc:identifier>
<dc:identifier>10.1007/s12559-017-9501-5</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Cognitive Computation. 2017;9:712–720</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</dc:rights>
<dc:rights>Attribution 4.0 International</dc:rights>
<dc:publisher>Springer Nature</dc:publisher>
</qdc:qualifieddc>
<?xml version="1.0" encoding="UTF-8" ?>
<rdf:RDF schemaLocation="http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd">
<ow:Publication about="oai:repositori.tecnocampus.cat:20.500.12367/2529">
<dc:title>A comparative study of in-air trajectories at short and long distances in online handwriting</dc:title>
<dc:creator>Alonso-Martinez, Carlos</dc:creator>
<dc:creator>Faundez-Zanuy, Marcos</dc:creator>
<dc:creator>Mekyska, Jiri</dc:creator>
<dc:description>Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</dc:description>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2023-12-04T10:36:40Z</dc:date>
<dc:date>2017</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</dc:identifier>
<dc:identifier>1866-9964</dc:identifier>
<dc:identifier>http://hdl.handle.net/20.500.12367/2529</dc:identifier>
<dc:identifier>10.1007/s12559-017-9501-5</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Cognitive Computation. 2017;9:712–720</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</dc:rights>
<dc:rights>Attribution 4.0 International</dc:rights>
<dc:publisher>Springer Nature</dc:publisher>
</ow:Publication>
</rdf:RDF>
<?xml version="1.0" encoding="UTF-8" ?>
<metadata schemaLocation="http://www.lyncode.com/xoai http://www.lyncode.com/xsd/xoai.xsd">
<element name="dc">
<element name="contributor">
<element name="author">
<element name="none">
<field name="value">Alonso-Martinez, Carlos</field>
<field name="authority">bab09de0-91a6-46fd-bf4f-5f51a361b1cf</field>
<field name="confidence">600</field>
<field name="orcid_id">0000-0002-3759-5103</field>
<field name="value">Faundez-Zanuy, Marcos</field>
<field name="authority">bd6ec996-6f01-492f-9fdb-e2c4026d3d65</field>
<field name="confidence">600</field>
<field name="orcid_id">0000-0003-0605-1282</field>
<field name="value">Mekyska, Jiri</field>
<field name="authority">34abaf20-0e22-488a-9415-a97f3dd5d3aa</field>
<field name="confidence">600</field>
<field name="orcid_id">0000-0002-6195-193X</field>
</element>
</element>
</element>
<element name="date">
<element name="accessioned">
<element name="none">
<field name="value">2023-12-04T10:36:40Z</field>
</element>
</element>
<element name="available">
<element name="none">
<field name="value">2023-12-04T10:36:40Z</field>
</element>
</element>
<element name="issued">
<element name="none">
<field name="value">2017</field>
</element>
</element>
</element>
<element name="identifier">
<element name="citation">
<element name="ca">
<field name="value">Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. A comparative study of in-air trajectories at short and long distances in online handwriting. Cogn Comput. 2017;9:712–720: DOI: 10.1007/s12559-017-9501-5</field>
</element>
</element>
<element name="issn">
<element name="ca">
<field name="value">1866-9964</field>
</element>
</element>
<element name="uri">
<element name="none">
<field name="value">http://hdl.handle.net/20.500.12367/2529</field>
</element>
</element>
<element name="doi">
<element name="ca">
<field name="value">10.1007/s12559-017-9501-5</field>
</element>
</element>
</element>
<element name="description">
<element name="abstract">
<element name="ca">
<field name="value">Existing literature about online handwriting analysis to support pathology diagnosis has taken advantage of in-air trajectories. A similar situation occurred in biometric security applications where the goal is to identify or verify an individual using his signature or handwriting. These studies do not consider the distance of the pen tip to the writing surface. This is due to the fact that current acquisition devices do not provide height formation. However, it is quite straightforward to differentiate movements at two different heights (a) short distance: height lower or equal to 1 cm above a surface of digitizer, the digitizer provides x and y coordinates; (b) long distance: height exceeding 1 cm, the only information available is a time stamp that indicates the time that a specific stroke has spent at long distance. [...]</field>
</element>
</element>
<element name="version">
<element name="ca">
<field name="value">info:eu-repo/semantics/publishedVersion</field>
</element>
</element>
</element>
<element name="format">
<element name="extent">
<element name="ca">
<field name="value">9 p.</field>
</element>
</element>
</element>
<element name="language">
<element name="iso">
<element name="ca">
<field name="value">eng</field>
</element>
</element>
</element>
<element name="publisher">
<element name="ca">
<field name="value">Springer Nature</field>
</element>
</element>
<element name="relation">
<element name="ispartof">
<element name="ca">
<field name="value">Cognitive Computation. 2017;9:712–720</field>
</element>
</element>
</element>
<element name="rights">
<element name="ca">
<field name="value">(c) Alonso-Martinez C, Faundez-Zanuy M, Mekyska J. 2018, corrected publication June/2018</field>
</element>
<element name="*">
<field name="value">Attribution 4.0 International</field>
</element>
<element name="uri">
<element name="*">
<field name="value">http://creativecommons.org/licenses/by/4.0/</field>
</element>
</element>
<element name="accessLevel">
<element name="none">
<field name="value">info:eu-repo/semantics/openAccess</field>
</element>
</element>
</element>
<element name="subject">
<element name="other">
<element name="ca">
<field name="value">Handwriting</field>
<field name="value">Biometrics</field>
<field name="value">In-air trajectories</field>
</element>
</element>
</element>
<element name="title">
<element name="ca">
<field name="value">A comparative study of in-air trajectories at short and long distances in online handwriting</field>
</element>
</element>
<element name="type">
<element name="ca">
<field name="value">info:eu-repo/semantics/article</field>
</element>
</element>
<element name="embargo">
<element name="terms">
<element name="ca">
<field name="value">cap</field>
</element>
</element>
</element>
</element>
<element name="bundles">
<element name="bundle">
<field name="name">ORIGINAL</field>
<element name="bitstreams">
<element name="bitstream">
<field name="name">alonso_cogncomput_comp.pdf</field>
<field name="originalName">alonso_cogncomput_comp.pdf</field>
<field name="format">application/pdf</field>
<field name="size">654669</field>
<field name="url">https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/1/alonso_cogncomput_comp.pdf</field>
<field name="checksum">2e48a5b719039d15adaa46b8b8251d75</field>
<field name="checksumAlgorithm">MD5</field>
<field name="sid">1</field>
<field name="drm">open access</field>
</element>
</element>
</element>
<element name="bundle">
<field name="name">CC-LICENSE</field>
<element name="bitstreams">
<element name="bitstream">
<field name="name">license_rdf</field>
<field name="originalName">license_rdf</field>
<field name="format">application/rdf+xml; charset=utf-8</field>
<field name="size">908</field>
<field name="url">https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/2/license_rdf</field>
<field name="checksum">0175ea4a2d4caec4bbcc37e300941108</field>
<field name="checksumAlgorithm">MD5</field>
<field name="sid">2</field>
<field name="drm">open access</field>
</element>
</element>
</element>
<element name="bundle">
<field name="name">TEXT</field>
<element name="bitstreams">
<element name="bitstream">
<field name="name">alonso_cogncomput_comp.pdf.txt</field>
<field name="originalName">alonso_cogncomput_comp.pdf.txt</field>
<field name="description">Extracted text</field>
<field name="format">text/plain</field>
<field name="size">29976</field>
<field name="url">https://repositori.tecnocampus.cat/bitstream/20.500.12367/2529/3/alonso_cogncomput_comp.pdf.txt</field>
<field name="checksum">3dabc23fed1ac19f758c65c5455bbfc7</field>
<field name="checksumAlgorithm">MD5</field>
<field name="sid">3</field>
<field name="drm">open access</field>
</element>
</element>
</element>
</element>
<element name="others">
<field name="handle">20.500.12367/2529</field>
<field name="identifier">oai:repositori.tecnocampus.cat:20.500.12367/2529</field>
<field name="lastModifyDate">2023-12-05 04:00:42.26</field>
<field name="drm">open access</field>
</element>
<element name="repository">
<field name="name">TECNOCAMPUS</field>
<field name="mail">pir@csuc.cat</field>
</element>
</metadata>