Ontology type: schema:Chapter
2014
AUTHORSDaiki Maemori , Lope Ben Porquis , Masashi Konyo , Satoshi Tadokoro
ABSTRACTHumans can perceive external forces applied on a grasping tool based on skin pressure distribution at multiple contact areas during grasp. The authors have tried to represent external forces and torques by controlling the skin pressure distributions using suction stimuli and confirmed the potential but in a heuristic manner. In this paper, we investigate an improved method of skin stimulation based on a combination of psychophysical experiments and mechanical simulation. We focus on a simplification method of the complex strain energy density (SED) distribution at the contact areas with four quadrant values (SED index). The relationship between suction pressure and SED index was achieved by connecting the experiment and the mechanical simulation. We confirmed that a suitable SED index could represent the magnitudes of forces in multiple directions with a linear function. Experimental results also showed that the proposed method could represent arbitrary directions between pairs of the orthogonal axes. More... »
PAGES285-294
Haptics: Neuroscience, Devices, Modeling, and Applications
ISBN
978-3-662-44195-4
978-3-662-44196-1
http://scigraph.springernature.com/pub.10.1007/978-3-662-44196-1_35
DOIhttp://dx.doi.org/10.1007/978-3-662-44196-1_35
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1035237749
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Clinical Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Tohoku University",
"id": "https://www.grid.ac/institutes/grid.69566.3a",
"name": [
"Tohoku University"
],
"type": "Organization"
},
"familyName": "Maemori",
"givenName": "Daiki",
"id": "sg:person.016650240635.52",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016650240635.52"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tohoku University",
"id": "https://www.grid.ac/institutes/grid.69566.3a",
"name": [
"Tohoku University"
],
"type": "Organization"
},
"familyName": "Porquis",
"givenName": "Lope Ben",
"id": "sg:person.010677332147.04",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010677332147.04"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tohoku University",
"id": "https://www.grid.ac/institutes/grid.69566.3a",
"name": [
"Tohoku University"
],
"type": "Organization"
},
"familyName": "Konyo",
"givenName": "Masashi",
"id": "sg:person.01101070023.41",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01101070023.41"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tohoku University",
"id": "https://www.grid.ac/institutes/grid.69566.3a",
"name": [
"Tohoku University"
],
"type": "Organization"
},
"familyName": "Tadokoro",
"givenName": "Satoshi",
"id": "sg:person.013454033251.77",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013454033251.77"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/978-3-642-14064-8_2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006827453",
"https://doi.org/10.1007/978-3-642-14064-8_2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00221-005-0259-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031631584",
"https://doi.org/10.1007/s00221-005-0259-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00221-005-0259-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031631584",
"https://doi.org/10.1007/s00221-005-0259-8"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1115/1.2795945",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1062082306"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/robot.2004.1308040",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094989275"
],
"type": "CreativeWork"
}
],
"datePublished": "2014",
"datePublishedReg": "2014-01-01",
"description": "Humans can perceive external forces applied on a grasping tool based on skin pressure distribution at multiple contact areas during grasp. The authors have tried to represent external forces and torques by controlling the skin pressure distributions using suction stimuli and confirmed the potential but in a heuristic manner. In this paper, we investigate an improved method of skin stimulation based on a combination of psychophysical experiments and mechanical simulation. We focus on a simplification method of the complex strain energy density (SED) distribution at the contact areas with four quadrant values (SED index). The relationship between suction pressure and SED index was achieved by connecting the experiment and the mechanical simulation. We confirmed that a suitable SED index could represent the magnitudes of forces in multiple directions with a linear function. Experimental results also showed that the proposed method could represent arbitrary directions between pairs of the orthogonal axes.",
"editor": [
{
"familyName": "Auvray",
"givenName": "Malika",
"type": "Person"
},
{
"familyName": "Duriez",
"givenName": "Christian",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-662-44196-1_35",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-662-44195-4",
"978-3-662-44196-1"
],
"name": "Haptics: Neuroscience, Devices, Modeling, and Applications",
"type": "Book"
},
"name": "A Multi-DOF Haptic Representation Using Suction Pressure Stimuli on Finger Pads",
"pagination": "285-294",
"productId": [
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-662-44196-1_35"
]
},
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"a7db2dd562726133f0e0c7cab7c3256232298f60ee9dd084fdfe72185411c255"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1035237749"
]
}
],
"publisher": {
"location": "Berlin, Heidelberg",
"name": "Springer Berlin Heidelberg",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-662-44196-1_35",
"https://app.dimensions.ai/details/publication/pub.1035237749"
],
"sdDataset": "chapters",
"sdDatePublished": "2019-04-15T10:36",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8659_00000265.jsonl",
"type": "Chapter",
"url": "http://link.springer.com/10.1007/978-3-662-44196-1_35"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-662-44196-1_35'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-662-44196-1_35'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-662-44196-1_35'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-662-44196-1_35'
This table displays all metadata directly associated to this object as RDF triples.
105 TRIPLES
23 PREDICATES
31 URIs
20 LITERALS
8 BLANK NODES