{"id":"https://openalex.org/W4400352376","doi":"https://doi.org/10.3390/s24134378","title":"Glove-Net: Enhancing Grasp Classification with Multisensory Data and Deep Learning Approach","display_name":"Glove-Net: Enhancing Grasp Classification with Multisensory Data and Deep Learning Approach","publication_year":2024,"publication_date":"2024-07-05","ids":{"openalex":"https://openalex.org/W4400352376","doi":"https://doi.org/10.3390/s24134378","pmid":"https://pubmed.ncbi.nlm.nih.gov/39001157"},"language":"en","primary_location":{"id":"doi:10.3390/s24134378","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24134378","pdf_url":"https://www.mdpi.com/1424-8220/24/13/4378/pdf?version=1720428483","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/13/4378/pdf?version=1720428483","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095853182","display_name":"Subhash Pratap","orcid":"https://orcid.org/0000-0002-9904-4497"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]},{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["IN","JP"],"is_corresponding":true,"raw_author_name":"Subhash Pratap","raw_affiliation_strings":["Department of Mechanical Engineering, Gifu University, Gifu 501-1193, Japan","Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, India"],"raw_orcid":"https://orcid.org/0000-0002-9904-4497","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Gifu University, Gifu 501-1193, Japan","institution_ids":["https://openalex.org/I42405503"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052907240","display_name":"Jyotindra Narayan","orcid":"https://orcid.org/0000-0002-2499-6039"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]},{"id":"https://openalex.org/I54009628","display_name":"University of Bayreuth","ror":"https://ror.org/0234wmv40","country_code":"DE","type":"education","lineage":["https://openalex.org/I54009628"]}],"countries":["DE","GB"],"is_corresponding":true,"raw_author_name":"Jyotindra Narayan","raw_affiliation_strings":["Chair of Digital Health, Universit\u00e4t Bayreuth, 95445 Bayreuth, Germany","Department of Computing, Imperial College London, London SW7 2RH, UK"],"raw_orcid":"https://orcid.org/0000-0002-2499-6039","affiliations":[{"raw_affiliation_string":"Chair of Digital Health, Universit\u00e4t Bayreuth, 95445 Bayreuth, Germany","institution_ids":["https://openalex.org/I54009628"]},{"raw_affiliation_string":"Department of Computing, Imperial College London, London SW7 2RH, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041478361","display_name":"Yoshiyuki Hatta","orcid":"https://orcid.org/0000-0001-7077-5264"},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiyuki Hatta","raw_affiliation_strings":["Department of Mechanical Engineering, Gifu University, Gifu 501-1193, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Gifu University, Gifu 501-1193, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047042841","display_name":"Kazuaki Ito","orcid":"https://orcid.org/0000-0002-8977-3709"},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuaki Ito","raw_affiliation_strings":["Department of Mechanical Engineering, Gifu University, Gifu 501-1193, Japan"],"raw_orcid":"https://orcid.org/0000-0002-8977-3709","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Gifu University, Gifu 501-1193, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083452335","display_name":"Shyamanta M. Hazarika","orcid":"https://orcid.org/0000-0003-4547-6013"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shyamanta M. Hazarika","raw_affiliation_strings":["Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, India"],"raw_orcid":"https://orcid.org/0000-0003-4547-6013","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, India","institution_ids":["https://openalex.org/I1317621060"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052907240","https://openalex.org/A5095853182"],"corresponding_institution_ids":["https://openalex.org/I1317621060","https://openalex.org/I42405503","https://openalex.org/I47508984","https://openalex.org/I54009628"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":4.8008,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.9559296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"24","issue":"13","first_page":"4378","last_page":"4378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.903425931930542},{"id":"https://openalex.org/keywords/wired-glove","display_name":"Wired glove","score":0.8127923011779785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.724612295627594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7011991739273071},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.643859326839447},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5199959874153137},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4596952497959137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4453752338886261},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37525296211242676},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3374062776565552},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.23567771911621094},{"id":"https://openalex.org/keywords/virtual-reality","display_name":"Virtual reality","score":0.21451908349990845}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.903425931930542},{"id":"https://openalex.org/C107953548","wikidata":"https://www.wikidata.org/wiki/Q1172433","display_name":"Wired glove","level":3,"score":0.8127923011779785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.724612295627594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7011991739273071},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.643859326839447},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5199959874153137},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4596952497959137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4453752338886261},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37525296211242676},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3374062776565552},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.23567771911621094},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.21451908349990845},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005385","descriptor_name":"Fingers","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D005385","descriptor_name":"Fingers","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D005385","descriptor_name":"Fingers","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D005385","descriptor_name":"Fingers","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011187","descriptor_name":"Posture","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D011187","descriptor_name":"Posture","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D011187","descriptor_name":"Posture","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D011187","descriptor_name":"Posture","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D012371","descriptor_name":"Robotics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012371","descriptor_name":"Robotics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012371","descriptor_name":"Robotics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012371","descriptor_name":"Robotics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018737","descriptor_name":"Hand Strength","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D018737","descriptor_name":"Hand Strength","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D018737","descriptor_name":"Hand Strength","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D018737","descriptor_name":"Hand Strength","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.3390/s24134378","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24134378","pdf_url":"https://www.mdpi.com/1424-8220/24/13/4378/pdf?version=1720428483","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:39001157","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39001157","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11244365","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11244365","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11244365/pdf/sensors-24-04378.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:5dde3eb949994bb6b6578cf0560b6837","is_oa":true,"landing_page_url":"https://doaj.org/article/5dde3eb949994bb6b6578cf0560b6837","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 13, p 4378 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24134378","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24134378","pdf_url":"https://www.mdpi.com/1424-8220/24/13/4378/pdf?version=1720428483","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400352376.pdf"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1755916113","https://openalex.org/W1981066923","https://openalex.org/W2052863493","https://openalex.org/W2080407376","https://openalex.org/W2144573888","https://openalex.org/W2211217408","https://openalex.org/W2282481780","https://openalex.org/W2313507061","https://openalex.org/W2556365147","https://openalex.org/W2775357942","https://openalex.org/W2776146695","https://openalex.org/W2793282010","https://openalex.org/W2886622560","https://openalex.org/W2946165673","https://openalex.org/W2946178047","https://openalex.org/W2947434510","https://openalex.org/W2959304487","https://openalex.org/W2967458152","https://openalex.org/W2995983596","https://openalex.org/W2999224157","https://openalex.org/W3006672203","https://openalex.org/W3012366945","https://openalex.org/W3035378577","https://openalex.org/W3044457538","https://openalex.org/W3045185600","https://openalex.org/W3046993022","https://openalex.org/W3099587965","https://openalex.org/W3106591298","https://openalex.org/W3130831275","https://openalex.org/W3131212828","https://openalex.org/W3142504421","https://openalex.org/W3158050854","https://openalex.org/W3158415928","https://openalex.org/W3159051549","https://openalex.org/W3196106467","https://openalex.org/W3196461002","https://openalex.org/W3198290822","https://openalex.org/W3204399832","https://openalex.org/W4200356177","https://openalex.org/W4205646621","https://openalex.org/W4213113494","https://openalex.org/W4214579445","https://openalex.org/W4221049285","https://openalex.org/W4225691622","https://openalex.org/W4226506318","https://openalex.org/W4281562441","https://openalex.org/W4285285244","https://openalex.org/W4294286438","https://openalex.org/W4312550647","https://openalex.org/W4318970028","https://openalex.org/W4319781001","https://openalex.org/W4319999824","https://openalex.org/W4324334783","https://openalex.org/W4388220042","https://openalex.org/W4388758254","https://openalex.org/W4392563834","https://openalex.org/W4395070010","https://openalex.org/W6638084879","https://openalex.org/W6688344122","https://openalex.org/W6781510497","https://openalex.org/W6781994667"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W4399251553","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4399254932"],"abstract_inverted_index":{"Grasp":[0],"classification":[1,64,158,222],"is":[2],"pivotal":[3],"for":[4,88,171,186,237,251],"understanding":[5,244],"human":[6],"interactions":[7],"with":[8,10,54,117,199],"objects,":[9],"wide-ranging":[11],"applications":[12],"in":[13,51,124,233],"robotics,":[14],"prosthetics,":[15],"and":[16,39,77,105,151,155,167,174,184,204,223,248],"rehabilitation.":[17],"This":[18,108],"study":[19,138,145],"introduces":[20],"a":[21,25,84],"novel":[22],"methodology":[23],"utilizing":[24,69,73],"multisensory":[26,235],"data":[27,45,236],"glove":[28],"to":[29,96],"capture":[30],"intricate":[31,130],"grasp":[32,52,70,74,90,221,239],"dynamics,":[33],"including":[34],"finger":[35],"posture":[36,71],"bending":[37],"angles":[38],"fingertip":[40],"forces.":[41],"Our":[42,137],"dataset":[43],"comprises":[44],"collected":[46],"from":[47,141],"10":[48],"participants":[49],"engaging":[50],"trials":[53],"24":[55],"objects":[56],"using":[57],"the":[58,98,118,129,157,187,191,207,217,225,228],"YCB":[59],"object":[60],"set.":[61],"We":[62,81,153],"evaluate":[63],"performance":[65,198],"under":[66],"three":[67],"scenarios:":[68,162],"alone,":[72,76],"force":[75],"combining":[78],"both":[79,103],"modalities.":[80],"propose":[82],"Glove-Net,":[83],"hybrid":[85,192,230],"CNN-BiLSTM":[86,193],"architecture":[87],"classifying":[89],"patterns":[91],"within":[92,133],"our":[93,134,214],"dataset,":[94],"aiming":[95],"harness":[97],"unique":[99],"advantages":[100],"offered":[101],"by":[102],"CNNs":[104],"BiLSTM":[106,125],"networks.":[107],"model":[109,149,195],"seamlessly":[110],"integrates":[111],"CNNs\u2019":[112],"spatial":[113],"feature":[114],"extraction":[115],"capabilities":[116],"temporal":[119],"sequence":[120],"learning":[121],"strengths":[122],"inherent":[123],"networks,":[126],"effectively":[127],"addressing":[128],"dependencies":[131],"present":[132],"grasping":[135],"data.":[136],"includes":[139],"findings":[140],"an":[142],"extensive":[143],"ablation":[144],"aimed":[146],"at":[147],"optimizing":[148],"configurations":[150],"hyperparameters.":[152],"quantify":[154],"compare":[156],"accuracy":[159],"across":[160,206],"these":[161],"CNN":[163],"achieved":[164],"88.09%,":[165],"69.38%,":[166],"93.51%":[168],"testing":[169],"accuracies":[170,180,200],"posture-only,":[172],"force-only,":[173],"combined":[175],"data,":[176],"respectively.":[177],"LSTM":[178],"exhibited":[179],"of":[181,201,219,227,245],"86.02%,":[182],"70.52%,":[183],"92.19%":[185],"same":[188],"scenarios.":[189,209],"Notably,":[190],"proposed":[194,229],"demonstrated":[196],"superior":[197],"90.83%,":[202],"73.12%,":[203],"98.75%":[205],"respective":[208],"Through":[210],"rigorous":[211],"numerical":[212],"experimentation,":[213],"results":[215],"underscore":[216],"significance":[218],"multimodal":[220],"highlight":[224],"efficacy":[226],"Glove-Net":[231],"architectures":[232],"leveraging":[234],"precise":[238],"recognition.":[240],"These":[241],"insights":[242],"advance":[243],"human\u2013machine":[246],"interaction":[247],"hold":[249],"promise":[250],"diverse":[252],"real-world":[253],"applications.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}