A brain-computer interface with vibrotactile biofeedback for haptic information
Identifieur interne : 000C53 ( Ncbi/Merge ); précédent : 000C52; suivant : 000C54A brain-computer interface with vibrotactile biofeedback for haptic information
Auteurs : Aniruddha Chatterjee [États-Unis] ; Vikram Aggarwal [États-Unis] ; Ander Ramos [Espagne] ; Soumyadipta Acharya [États-Unis] ; Nitish V. Thakor [États-Unis]Source :
- Journal of NeuroEngineering and Rehabilitation [ 1743-0003 ] ; 2007.
English descriptors
- KwdEn :
- MESH :
- methods : Biofeedback, Psychology, Electroencephalography.
- physiology : Brain, Evoked Potentials, Somatosensory, Imagination, Touch.
- Adult, Female, Humans, Male, Task Performance and Analysis, User-Computer Interface, Vibration.
Abstract
It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only
A Mu-rhythm based BCI using a motor imagery paradigm was used to control the position of a virtual cursor. The cursor position was shown visually as well as transmitted haptically by modulating the intensity of a vibrotactile stimulus to the upper limb. A total of six subjects operated the BCI in a two-stage targeting task, receiving only vibrotactile biofeedback of performance. The location of the vibration was also systematically varied between the left and right arms to investigate location-dependent effects on performance.
Subjects are able to control the BCI using only vibrotactile feedback with an average accuracy of 56% and as high as 72%. These accuracies are significantly higher than the 15% predicted by random chance if the subject had no voluntary control of their Mu-rhythm. The results of this study demonstrate that vibrotactile feedback is an effective biofeedback modality to operate a BCI using motor imagery. In addition, the study shows that placement of the vibrotactile stimulation on the biceps ipsilateral or contralateral to the motor imagery introduces a significant bias in the BCI accuracy. This bias is consistent with a drop in performance generated by stimulation of the contralateral limb. Users demonstrated the capability to overcome this bias with training.
Url:
DOI: 10.1186/1743-0003-4-40
PubMed: 17941986
PubMed Central: 2104531
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Thakor</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author></analytic><series><title level="j">Journal of NeuroEngineering and Rehabilitation</title><idno type="eISSN">1743-0003</idno><imprint><date when="2007">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Biofeedback, Psychology (methods)</term><term>Brain (physiology)</term><term>Electroencephalography (methods)</term><term>Evoked Potentials, Somatosensory (physiology)</term><term>Female</term><term>Humans</term><term>Imagination (physiology)</term><term>Male</term><term>Task Performance and Analysis</term><term>Touch (physiology)</term><term>User-Computer Interface</term><term>Vibration</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Biofeedback, Psychology</term><term>Electroencephalography</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Brain</term><term>Evoked Potentials, Somatosensory</term><term>Imagination</term><term>Touch</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Female</term><term>Humans</term><term>Male</term><term>Task Performance and Analysis</term><term>User-Computer Interface</term><term>Vibration</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only <italic>vibrotactile feedback</italic>, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy.</p></sec><sec sec-type="methods"><title>Methods</title><p>A Mu-rhythm based BCI using a motor imagery paradigm was used to control the position of a virtual cursor. The cursor position was shown visually as well as transmitted haptically by modulating the intensity of a vibrotactile stimulus to the upper limb. A total of six subjects operated the BCI in a two-stage targeting task, receiving only vibrotactile biofeedback of performance. The location of the vibration was also systematically varied between the left and right arms to investigate location-dependent effects on performance.</p></sec><sec><title>Results and Conclusion</title><p>Subjects are able to control the BCI using only vibrotactile feedback with an average accuracy of 56% and as high as 72%. These accuracies are significantly higher than the 15% predicted by random chance if the subject had no voluntary control of their Mu-rhythm. The results of this study demonstrate that vibrotactile feedback is an effective biofeedback modality to operate a BCI using motor imagery. In addition, the study shows that placement of the vibrotactile stimulation on the biceps ipsilateral or contralateral to the motor imagery introduces a significant bias in the BCI accuracy. This bias is consistent with a drop in performance generated by stimulation of the contralateral limb. Users demonstrated the capability to overcome this bias with training.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><double pmid="17941986"><pmc><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A brain-computer interface with vibrotactile biofeedback for haptic information</title><author><name sortKey="Chatterjee, Aniruddha" sort="Chatterjee, Aniruddha" uniqKey="Chatterjee A" first="Aniruddha" last="Chatterjee">Aniruddha Chatterjee</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Aggarwal, Vikram" sort="Aggarwal, Vikram" uniqKey="Aggarwal V" first="Vikram" last="Aggarwal">Vikram Aggarwal</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Ramos, Ander" sort="Ramos, Ander" uniqKey="Ramos A" first="Ander" last="Ramos">Ander Ramos</name><affiliation wicri:level="1"><nlm:aff id="I2">Department of Biomedical Engineering, Fatronik Technological Foundation, Spain</nlm:aff><country xml:lang="fr">Espagne</country><wicri:regionArea>Department of Biomedical Engineering, Fatronik Technological Foundation</wicri:regionArea><wicri:noRegion>Fatronik Technological Foundation</wicri:noRegion></affiliation></author><author><name sortKey="Acharya, Soumyadipta" sort="Acharya, Soumyadipta" uniqKey="Acharya S" first="Soumyadipta" last="Acharya">Soumyadipta Acharya</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Thakor, Nitish V" sort="Thakor, Nitish V" uniqKey="Thakor N" first="Nitish V" last="Thakor">Nitish V. Thakor</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">17941986</idno><idno type="pmc">2104531</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2104531</idno><idno type="RBID">PMC:2104531</idno><idno type="doi">10.1186/1743-0003-4-40</idno><date when="2007">2007</date><idno type="wicri:Area/Pmc/Corpus">000B40</idno><idno type="wicri:Area/Pmc/Curation">000B40</idno><idno type="wicri:Area/Pmc/Checkpoint">002489</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A brain-computer interface with vibrotactile biofeedback for haptic information</title><author><name sortKey="Chatterjee, Aniruddha" sort="Chatterjee, Aniruddha" uniqKey="Chatterjee A" first="Aniruddha" last="Chatterjee">Aniruddha Chatterjee</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Aggarwal, Vikram" sort="Aggarwal, Vikram" uniqKey="Aggarwal V" first="Vikram" last="Aggarwal">Vikram Aggarwal</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Ramos, Ander" sort="Ramos, Ander" uniqKey="Ramos A" first="Ander" last="Ramos">Ander Ramos</name><affiliation wicri:level="1"><nlm:aff id="I2">Department of Biomedical Engineering, Fatronik Technological Foundation, Spain</nlm:aff><country xml:lang="fr">Espagne</country><wicri:regionArea>Department of Biomedical Engineering, Fatronik Technological Foundation</wicri:regionArea><wicri:noRegion>Fatronik Technological Foundation</wicri:noRegion></affiliation></author><author><name sortKey="Acharya, Soumyadipta" sort="Acharya, Soumyadipta" uniqKey="Acharya S" first="Soumyadipta" last="Acharya">Soumyadipta Acharya</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Thakor, Nitish V" sort="Thakor, Nitish V" uniqKey="Thakor N" first="Nitish V" last="Thakor">Nitish V. Thakor</name><affiliation wicri:level="2"><nlm:aff id="I1">Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author></analytic><series><title level="j">Journal of NeuroEngineering and Rehabilitation</title><idno type="eISSN">1743-0003</idno><imprint><date when="2007">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only <italic>vibrotactile feedback</italic>, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy.</p></sec><sec sec-type="methods"><title>Methods</title><p>A Mu-rhythm based BCI using a motor imagery paradigm was used to control the position of a virtual cursor. The cursor position was shown visually as well as transmitted haptically by modulating the intensity of a vibrotactile stimulus to the upper limb. A total of six subjects operated the BCI in a two-stage targeting task, receiving only vibrotactile biofeedback of performance. The location of the vibration was also systematically varied between the left and right arms to investigate location-dependent effects on performance.</p></sec><sec><title>Results and Conclusion</title><p>Subjects are able to control the BCI using only vibrotactile feedback with an average accuracy of 56% and as high as 72%. These accuracies are significantly higher than the 15% predicted by random chance if the subject had no voluntary control of their Mu-rhythm. The results of this study demonstrate that vibrotactile feedback is an effective biofeedback modality to operate a BCI using motor imagery. In addition, the study shows that placement of the vibrotactile stimulation on the biceps ipsilateral or contralateral to the motor imagery introduces a significant bias in the BCI accuracy. This bias is consistent with a drop in performance generated by stimulation of the contralateral limb. Users demonstrated the capability to overcome this bias with training.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI></pmc><pubmed><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A brain-computer interface with vibrotactile biofeedback for haptic information.</title><author><name sortKey="Chatterjee, Aniruddha" sort="Chatterjee, Aniruddha" uniqKey="Chatterjee A" first="Aniruddha" last="Chatterjee">Aniruddha Chatterjee</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA. ani.chatterjee@gmail.com</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Aggarwal, Vikram" sort="Aggarwal, Vikram" uniqKey="Aggarwal V" first="Vikram" last="Aggarwal">Vikram Aggarwal</name></author><author><name sortKey="Ramos, Ander" sort="Ramos, Ander" uniqKey="Ramos A" first="Ander" last="Ramos">Ander Ramos</name></author><author><name sortKey="Acharya, Soumyadipta" sort="Acharya, Soumyadipta" uniqKey="Acharya S" first="Soumyadipta" last="Acharya">Soumyadipta Acharya</name></author><author><name sortKey="Thakor, Nitish V" sort="Thakor, Nitish V" uniqKey="Thakor N" first="Nitish V" last="Thakor">Nitish V. Thakor</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2007">2007</date><idno type="doi">10.1186/1743-0003-4-40</idno><idno type="RBID">pubmed:17941986</idno><idno type="pmid">17941986</idno><idno type="wicri:Area/PubMed/Corpus">001575</idno><idno type="wicri:Area/PubMed/Curation">001575</idno><idno type="wicri:Area/PubMed/Checkpoint">001505</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A brain-computer interface with vibrotactile biofeedback for haptic information.</title><author><name sortKey="Chatterjee, Aniruddha" sort="Chatterjee, Aniruddha" uniqKey="Chatterjee A" first="Aniruddha" last="Chatterjee">Aniruddha Chatterjee</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA. ani.chatterjee@gmail.com</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Aggarwal, Vikram" sort="Aggarwal, Vikram" uniqKey="Aggarwal V" first="Vikram" last="Aggarwal">Vikram Aggarwal</name></author><author><name sortKey="Ramos, Ander" sort="Ramos, Ander" uniqKey="Ramos A" first="Ander" last="Ramos">Ander Ramos</name></author><author><name sortKey="Acharya, Soumyadipta" sort="Acharya, Soumyadipta" uniqKey="Acharya S" first="Soumyadipta" last="Acharya">Soumyadipta Acharya</name></author><author><name sortKey="Thakor, Nitish V" sort="Thakor, Nitish V" uniqKey="Thakor N" first="Nitish V" last="Thakor">Nitish V. Thakor</name></author></analytic><series><title level="j">Journal of neuroengineering and rehabilitation</title><idno type="eISSN">1743-0003</idno><imprint><date when="2007" type="published">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Biofeedback, Psychology (methods)</term><term>Brain (physiology)</term><term>Electroencephalography (methods)</term><term>Evoked Potentials, Somatosensory (physiology)</term><term>Female</term><term>Humans</term><term>Imagination (physiology)</term><term>Male</term><term>Task Performance and Analysis</term><term>Touch (physiology)</term><term>User-Computer Interface</term><term>Vibration</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Biofeedback, Psychology</term><term>Electroencephalography</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Brain</term><term>Evoked Potentials, Somatosensory</term><term>Imagination</term><term>Touch</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Female</term><term>Humans</term><term>Male</term><term>Task Performance and Analysis</term><term>User-Computer Interface</term><term>Vibration</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only vibrotactile feedback, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy.</div></front></TEI></pubmed></double></record>Pour manipuler ce document sous Unix (Dilib)
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