Method and system to safely guide interventions in procedures the substrate whereof is neuronal plasticity


Ontology type: sgo:Patent     


Patent Info

DATE

N/A

AUTHORS

GARCIA MOLINA, ALBERTO , GARCIA RUDOLPH, ALEJANDRO , OPISSO SALLERAS, ELOY , ROIG ROVIRA, MARIA TERESA , TORMOS MUNOZ, JOSE MARIA

ABSTRACT

The method comprises the generation of a database with information regarding users in relation to interventions to be realised and responses to such realisation by users, and analysis thereof to generate candidate predictions from which to determine final or optimum predictions, carrying out said generation of candidate predictions and said subsequent determination of final predictions through corresponding stages of classification at different levels, based on heuristic rules. The system is planned to implement the method proposed by the first aspect of the invention. The method and the system are particularly applicable in procedures such as those relating to neurorehabilitation, neuroeducation/neurolearning or cognitive neurostimulation. More... »

Related SciGraph Publications

  • 1996-08. Bagging predictors in MACHINE LEARNING
  • 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/2008/3468", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "name": "GARCIA MOLINA, ALBERTO", 
            "type": "Person"
          }, 
          {
            "name": "GARCIA RUDOLPH, ALEJANDRO", 
            "type": "Person"
          }, 
          {
            "name": "OPISSO SALLERAS, ELOY", 
            "type": "Person"
          }, 
          {
            "name": "ROIG ROVIRA, MARIA TERESA", 
            "type": "Person"
          }, 
          {
            "name": "TORMOS MUNOZ, JOSE MARIA", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/bf00058655", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002929950", 
              "https://doi.org/10.1007/bf00058655"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00058655", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002929950", 
              "https://doi.org/10.1007/bf00058655"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "description": "

    The method comprises the generation of a database with information regarding users in relation to interventions to be realised and responses to such realisation by users, and analysis thereof to generate candidate predictions from which to determine final or optimum predictions, carrying out said generation of candidate predictions and said subsequent determination of final predictions through corresponding stages of classification at different levels, based on heuristic rules. The system is planned to implement the method proposed by the first aspect of the invention. The method and the system are particularly applicable in procedures such as those relating to neurorehabilitation, neuroeducation/neurolearning or cognitive neurostimulation.

    ", "id": "sg:patent.AU-2008363525-B2", "keywords": [ "method", "guide intervention", "substrate", "Neuronal Plasticity", "generation", "database", "user", "relation", "intervention", "prediction", "determination", "stage", "classification", "different level", "heuristic", "first aspect", "invention", "neurorehabilitation", "neurostimulation" ], "name": "Method and system to safely guide interventions in procedures the substrate whereof is neuronal plasticity", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.434620.7", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/AU-2008363525-B2" ], "sdDataset": "patents", "sdDatePublished": "2019-03-07T15:34", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com.uberresearch.data.dev.patents-pipeline/full_run_10/sn-export/5eb3e5a348d7f117b22cc85fb0b02730/0000100128-0000348334/json_export_962f20a5.jsonl", "type": "Patent" } ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    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/patent.AU-2008363525-B2'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.AU-2008363525-B2'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.AU-2008363525-B2'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.AU-2008363525-B2'


     

    This table displays all metadata directly associated to this object as RDF triples.

    60 TRIPLES      14 PREDICATES      33 URIs      26 LITERALS      2 BLANK NODES

    Subject Predicate Object
    1 sg:patent.AU-2008363525-B2 schema:about anzsrc-for:3468
    2 schema:author Na82e0eef88554d8888f23ec748c5b931
    3 schema:citation sg:pub.10.1007/bf00058655
    4 schema:description <p>The method comprises the generation of a database with information regarding users in relation to interventions to be realised and responses to such realisation by users, and analysis thereof to generate candidate predictions from which to determine final or optimum predictions, carrying out said generation of candidate predictions and said subsequent determination of final predictions through corresponding stages of classification at different levels, based on heuristic rules. The system is planned to implement the method proposed by the first aspect of the invention. The method and the system are particularly applicable in procedures such as those relating to neurorehabilitation, neuroeducation/neurolearning or cognitive neurostimulation.</p>
    5 schema:keywords Neuronal Plasticity
    6 classification
    7 database
    8 determination
    9 different level
    10 first aspect
    11 generation
    12 guide intervention
    13 heuristic
    14 intervention
    15 invention
    16 method
    17 neurorehabilitation
    18 neurostimulation
    19 prediction
    20 relation
    21 stage
    22 substrate
    23 user
    24 schema:name Method and system to safely guide interventions in procedures the substrate whereof is neuronal plasticity
    25 schema:recipient https://www.grid.ac/institutes/grid.434620.7
    26 schema:sameAs https://app.dimensions.ai/details/patent/AU-2008363525-B2
    27 schema:sdDatePublished 2019-03-07T15:34
    28 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    29 schema:sdPublisher Na4aa8e4ad32b4c1bad48e325460086f8
    30 sgo:license sg:explorer/license/
    31 sgo:sdDataset patents
    32 rdf:type sgo:Patent
    33 N37a49434770544a69eeff8d81b990040 rdf:first N7a6db762375243a2992425a2b8cda280
    34 rdf:rest rdf:nil
    35 N3cbf6e23995d4e3d96766c39f5995661 rdf:first N64ab9a5326874ea68b011e96e88e5f28
    36 rdf:rest N4541d0c43ae2496c97dc66ea10ae6a06
    37 N3ed95e6da5784f29a2a96913262ec5e2 schema:name ROIG ROVIRA, MARIA TERESA
    38 rdf:type schema:Person
    39 N4541d0c43ae2496c97dc66ea10ae6a06 rdf:first N3ed95e6da5784f29a2a96913262ec5e2
    40 rdf:rest N37a49434770544a69eeff8d81b990040
    41 N64ab9a5326874ea68b011e96e88e5f28 schema:name OPISSO SALLERAS, ELOY
    42 rdf:type schema:Person
    43 N6770a4464ab9415889d02c0590cb5fe9 schema:name GARCIA RUDOLPH, ALEJANDRO
    44 rdf:type schema:Person
    45 N7a6db762375243a2992425a2b8cda280 schema:name TORMOS MUNOZ, JOSE MARIA
    46 rdf:type schema:Person
    47 Na19ec17e9cd94ada966d9b3f3a272e26 schema:name GARCIA MOLINA, ALBERTO
    48 rdf:type schema:Person
    49 Na4aa8e4ad32b4c1bad48e325460086f8 schema:name Springer Nature - SN SciGraph project
    50 rdf:type schema:Organization
    51 Na82e0eef88554d8888f23ec748c5b931 rdf:first Na19ec17e9cd94ada966d9b3f3a272e26
    52 rdf:rest Nd6fe254f64684ca49b987ff90279904c
    53 Nd6fe254f64684ca49b987ff90279904c rdf:first N6770a4464ab9415889d02c0590cb5fe9
    54 rdf:rest N3cbf6e23995d4e3d96766c39f5995661
    55 anzsrc-for:3468 schema:inDefinedTermSet anzsrc-for:
    56 rdf:type schema:DefinedTerm
    57 sg:pub.10.1007/bf00058655 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002929950
    58 https://doi.org/10.1007/bf00058655
    59 rdf:type schema:CreativeWork
    60 https://www.grid.ac/institutes/grid.434620.7 schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...