{"id":"https://openalex.org/W4391013441","doi":"https://doi.org/10.48550/arxiv.2401.09239","title":"DaFoEs: Mixing Datasets towards the generalization of vision-state deep-learning Force Estimation in Minimally Invasive Robotic Surgery","display_name":"DaFoEs: Mixing Datasets towards the generalization of vision-state deep-learning Force Estimation in Minimally Invasive Robotic Surgery","publication_year":2024,"publication_date":"2024-01-17","ids":{"openalex":"https://openalex.org/W4391013441","doi":"https://doi.org/10.48550/arxiv.2401.09239"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2401.09239","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.09239","pdf_url":"https://arxiv.org/pdf/2401.09239","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2401.09239","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069960926","display_name":"Mikel De Iturrate Reyzabal","orcid":"https://orcid.org/0000-0001-9503-8834"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Reyzabal, Mikel De Iturrate","raw_affiliation_strings":["School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013169403","display_name":"Mingcong Chen","orcid":"https://orcid.org/0000-0001-9544-2589"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chen, Mingcong","raw_affiliation_strings":["School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101949444","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0003-1936-0981"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huang, Wei","raw_affiliation_strings":["School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082106258","display_name":"S\u00e9bastien Ourselin","orcid":"https://orcid.org/0000-0002-5694-5340"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ourselin, Sebastien","raw_affiliation_strings":["Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong","School of Biomedical Engineering and Imaging Sciences, King's College London, UK,"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong","institution_ids":[]},{"raw_affiliation_string":"School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107885739","display_name":"Hongbin Liu","orcid":"https://orcid.org/0009-0008-3041-370X"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Liu, Hongbin","raw_affiliation_strings":["School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Imaging Sciences, King's College London, UK,","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5069960926"],"corresponding_institution_ids":["https://openalex.org/I183935753"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10868","display_name":"Soft Robotics and Applications","score":0.9693999886512756,"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/T11984","display_name":"Anatomy and Medical Technology","score":0.9236000180244446,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7766145467758179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6418348550796509},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6080807447433472},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5063365697860718},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44371578097343445},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40114933252334595}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7766145467758179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6418348550796509},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6080807447433472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5063365697860718},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44371578097343445},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40114933252334595}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2401.09239","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.09239","pdf_url":"https://arxiv.org/pdf/2401.09239","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},{"id":"pmh:oai:kclpure.kcl.ac.uk:openaire/ad1ff9e8-2d1c-4c6c-ba53-0c7b6efbb1e7","is_oa":true,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/ad1ff9e8-2d1c-4c6c-ba53-0c7b6efbb1e7","pdf_url":"https://kclpure.kcl.ac.uk/ws/files/245787608/DaFoEs_Mixing_Datasets_Towards_DE_ITURRATE_REYZABAL_Accepted_GREEN_AAM_CC_BY_.pdf","source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"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":"De Iturrate Reyzabal, M, Chen, M, Huang, W, Ourselin, S & Liu, H 2024, 'DaFoEs : Mixing Datasets Towards the Generalization of Vision-State Deep-Learning Force Estimation in Minimally Invasive Robotic Surgery', IEEE Robotics and Automation Letters, vol. 9, no. 3. https://doi.org/10.48550/arXiv.2401.09239, https://doi.org/10.1109/LRA.2024.3356984","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"doi:10.48550/arxiv.2401.09239","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2401.09239","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2401.09239","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.09239","pdf_url":"https://arxiv.org/pdf/2401.09239","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3764824620","display_name":"Integrating Haptic and Visual Data for Low Latency transmission","funder_award_id":"2446549","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391013441.pdf","grobid_xml":"https://content.openalex.org/works/W4391013441.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1635908606","https://openalex.org/W2031342017","https://openalex.org/W2924316106","https://openalex.org/W2944287224","https://openalex.org/W2963527806","https://openalex.org/W3002559070","https://openalex.org/W3081167590","https://openalex.org/W3094502228","https://openalex.org/W3105959138","https://openalex.org/W3205320754","https://openalex.org/W4226188792","https://openalex.org/W4283311522","https://openalex.org/W4283692027","https://openalex.org/W4312872526","https://openalex.org/W4384159652","https://openalex.org/W4386314094","https://openalex.org/W4387731565","https://openalex.org/W4388304086"],"related_works":["https://openalex.org/W3099765033","https://openalex.org/W2989932438","https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W2186333919","https://openalex.org/W4387297750","https://openalex.org/W4321369474"],"abstract_inverted_index":{"Precisely":[0],"determining":[1],"the":[2,28,42,79,89,128,132,152,162,165,180,189,213,224,238,267,271],"contact":[3],"force":[4,48,206,229,258],"during":[5],"safe":[6],"interaction":[7],"in":[8,260],"Minimally":[9],"Invasive":[10],"Robotic":[11],"Surgery":[12],"(MIRS)":[13],"is":[14,243,262],"still":[15],"an":[16],"open":[17],"research":[18],"challenge.":[19],"Inspired":[20],"by":[21,131,245],"post-operative":[22],"qualitative":[23],"analysis":[24],"from":[25,91],"surgical":[26],"videos,":[27],"use":[29,146],"of":[30,41,81,140,164,208,226,235,240,270],"cross-modality":[31],"data":[32,105,182,242],"driven":[33],"deep":[34,82],"neural":[35,83],"network":[36],"models":[37,217],"has":[38,185],"been":[39],"one":[40],"newest":[43],"approaches":[44],"to":[45,87,99,126,160,177,179,232],"predict":[46,127],"sensorless":[47],"trends.":[49],"However,":[50,194],"these":[51],"methods":[52],"required":[53],"for":[54,78,107,212,228,256],"large":[55],"and":[56,103,155,210,215],"variable":[57,75,123],"datasets":[58],"which":[59],"are":[60],"not":[61],"currently":[62],"available.":[63],"In":[64,85,247],"this":[65],"paper,":[66],"we":[67,95,120,145,170,249],"present":[68,96,121],"a":[69,92,97,112,122,147,156,198,202,233,263],"new":[70,157,192],"vision-haptic":[71],"dataset":[72,109,115,174,195],"(DaFoEs)":[73],"with":[74,116,151,201],"soft":[76],"environments":[77],"training":[80,175,181],"models.":[84],"order":[86],"reduce":[88],"bias":[90],"single":[93,136,173],"dataset,":[94],"pipeline":[98],"generalize":[100],"different":[101,117],"vision":[102],"state":[104],"inputs":[106],"mixed":[108],"training,":[110,169],"using":[111,135],"previously":[113],"validated":[114],"setup.":[118],"Finally,":[119],"encoder-decoder":[124],"architecture":[125],"forces":[129],"done":[130],"laparoscopic":[133],"tool":[134],"input":[137,143],"or":[138],"sequence":[139],"inputs.":[141],"For":[142],"sequence,":[144],"recurrent":[148,214],"decoder,":[149],"named":[150],"prefix":[153],"R,":[154],"temporal":[158],"sampling":[159],"represent":[161],"acceleration":[163],"tool.":[166],"During":[167],"our":[168],"demonstrate":[171,250],"that":[172,251],"tends":[176],"overfit":[178],"domain,":[183],"but":[184],"difficulties":[186],"on":[187],"translating":[188],"results":[190],"across":[191],"domains.":[193],"mixing":[196,252],"presents":[197],"good":[199],"translation":[200],"mean":[203],"relative":[204],"estimated":[205],"error":[207],"5%":[209],"12%":[211],"non-recurrent":[216],"respectively.":[218],"Our":[219],"method,":[220],"also":[221],"marginally":[222],"increase":[223,244],"effectiveness":[225],"transformers":[227],"estimation":[230,259],"up":[231],"maximum":[234],"~15%,":[236],"as":[237],"volume":[239],"available":[241],"150%.":[246],"conclusion,":[248],"experimental":[253],"set":[254],"ups":[255],"vision-state":[257],"MIRS":[261],"possible":[264],"approach":[265],"towards":[266],"general":[268],"solution":[269],"problem.":[272]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2024-01-19T00:00:00"}
