A Simple and Accurate onset Detection Method for a Measured Bell-shaped Speed Profile
Identifieur interne : 001596 ( Ncbi/Curation ); précédent : 001595; suivant : 001597A Simple and Accurate onset Detection Method for a Measured Bell-shaped Speed Profile
Auteurs : Lior Botzer [Israël] ; Amir Karniel [Israël]Source :
- Frontiers in Neuroscience [ 1662-4548 ] ; 2009.
Abstract
Motor control neuroscientists measure limb trajectories and extract the onset of the movement for a variety of purposes. Such trajectories are often aligned relative to the onset of individual movement before the features of that movement are extracted and their properties are inspected. Onset detection is performed either manually or automatically, typically by selecting a velocity threshold. Here, we present a simple onset detection algorithm that is more accurate than the conventional velocity threshold technique. The proposed method is based on a simple regression and follows the minimum acceleration with constraints model, in which the initial phase of the bell-shaped movement is modeled by a cubic power of the time. We demonstrate the performance of the suggested method and compare it to the velocity threshold technique and to manual onset detection by a group of motor control experts. The database for this comparison consists of simulated minimum jerk trajectories and recorded reaching movements.
Url:
DOI: 10.3389/neuro.20.002.2009
PubMed: 20582285
PubMed Central: 2858598
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A Simple and Accurate onset Detection Method for a Measured Bell-shaped Speed Profile</title><author><name sortKey="Botzer, Lior" sort="Botzer, Lior" uniqKey="Botzer L" first="Lior" last="Botzer">Lior Botzer</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Department of Biomedical Engineering, Ben-Gurion University of the Negev</institution><country>Israel</country></nlm:aff><country xml:lang="fr">Israël</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Karniel, Amir" sort="Karniel, Amir" uniqKey="Karniel A" first="Amir" last="Karniel">Amir Karniel</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Department of Biomedical Engineering, Ben-Gurion University of the Negev</institution><country>Israel</country></nlm:aff><country xml:lang="fr">Israël</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">20582285</idno><idno type="pmc">2858598</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2858598</idno><idno type="RBID">PMC:2858598</idno><idno type="doi">10.3389/neuro.20.002.2009</idno><date when="2009">2009</date><idno type="wicri:Area/Pmc/Corpus">001E59</idno><idno type="wicri:Area/Pmc/Curation">001E59</idno><idno type="wicri:Area/Pmc/Checkpoint">002219</idno><idno type="wicri:Area/Ncbi/Merge">001596</idno><idno type="wicri:Area/Ncbi/Curation">001596</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A Simple and Accurate onset Detection Method for a Measured Bell-shaped Speed Profile</title><author><name sortKey="Botzer, Lior" sort="Botzer, Lior" uniqKey="Botzer L" first="Lior" last="Botzer">Lior Botzer</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Department of Biomedical Engineering, Ben-Gurion University of the Negev</institution><country>Israel</country></nlm:aff><country xml:lang="fr">Israël</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Karniel, Amir" sort="Karniel, Amir" uniqKey="Karniel A" first="Amir" last="Karniel">Amir Karniel</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Department of Biomedical Engineering, Ben-Gurion University of the Negev</institution><country>Israel</country></nlm:aff><country xml:lang="fr">Israël</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></analytic><series><title level="j">Frontiers in Neuroscience</title><idno type="ISSN">1662-4548</idno><idno type="eISSN">1662-453X</idno><imprint><date when="2009">2009</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Motor control neuroscientists measure limb trajectories and extract the onset of the movement for a variety of purposes. Such trajectories are often aligned relative to the onset of individual movement before the features of that movement are extracted and their properties are inspected. Onset detection is performed either manually or automatically, typically by selecting a velocity threshold. Here, we present a simple onset detection algorithm that is more accurate than the conventional velocity threshold technique. The proposed method is based on a simple regression and follows the minimum acceleration with constraints model, in which the initial phase of the bell-shaped movement is modeled by a cubic power of the time. We demonstrate the performance of the suggested method and compare it to the velocity threshold technique and to manual onset detection by a group of motor control experts. The database for this comparison consists of simulated minimum jerk trajectories and recorded reaching movements.
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