{"id":"https://openalex.org/W7162795316","doi":"https://doi.org/10.48550/arxiv.2605.29771","title":"Joint Angle Estimation with Customized Wristband Based on Online Incremental Learning","display_name":"Joint Angle Estimation with Customized Wristband Based on Online Incremental Learning","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162795316","doi":"https://doi.org/10.48550/arxiv.2605.29771"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29771","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29771","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.29771","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137320009","display_name":"Shuo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137338358","display_name":"Xiaobin Chen","orcid":"https://orcid.org/0009-0007-2944-9070"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiaobin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137379314","display_name":"Xiaoming Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Xiaoming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.22470000386238098,"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"}},"topics":[{"id":"https://openalex.org/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.22470000386238098,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.1370999962091446,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.09730000048875809,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.7526000142097473},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.6766999959945679},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5217999815940857},{"id":"https://openalex.org/keywords/wrist","display_name":"Wrist","score":0.5196999907493591},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4832000136375427},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4465999901294708},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.32739999890327454}],"concepts":[{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.7526000142097473},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6766999959945679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6384999752044678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6007000207901001},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5437999963760376},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5217999815940857},{"id":"https://openalex.org/C2778216619","wikidata":"https://www.wikidata.org/wiki/Q185706","display_name":"Wrist","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4832000136375427},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4465999901294708},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3625999987125397},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.29350000619888306},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29771","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29771","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.29771","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29771","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Intelligent":[0],"wearable":[1,32,39],"technology":[2],"plays":[3],"an":[4,69,100,208],"increasingly":[5],"important":[6],"role":[7],"in":[8,147,155,171,214],"human-computer":[9],"interaction,":[10],"motion,":[11],"and":[12,18,43,163,179,197],"health":[13],"monitoring.":[14],"To":[15],"ensure":[16],"comfort":[17],"practicality":[19],"of":[20,59,114,166,203,211],"use,":[21],"one":[22],"common":[23],"form":[24],"for":[25,55,112,139],"motion":[26],"monitoring":[27],"is":[28,75,127],"to":[29,45,47,136,149],"utilize":[30],"soft":[31],"sensors.":[33],"However,":[34],"many":[35],"research":[36],"applications":[37],"regarding":[38],"sensors":[40,190],"are":[41],"simplistic":[42],"difficult":[44],"adapt":[46],"different":[48,156,215],"situations.":[49],"This":[50,143],"study":[51],"proposes":[52],"a":[53,64,76],"system":[54,206],"estimating":[56],"the":[57,60,80,84,88,109,120,133,161,167,172,176,189,198,204],"angle":[58,117,141],"wrist":[61,90,115,199],"joint":[62,116,200],"using":[63,93],"customized":[65],"wristband":[66],"based":[67,86],"on":[68,87,175],"online":[70,94],"incremental":[71],"learning":[72],"approach.":[73],"It":[74],"two-stage":[77],"estimation":[78,113,202],"method:":[79],"first":[81],"stage":[82,107],"updates":[83],"model":[85,111,125,135],"wearer's":[89],"movement":[91],"characteristics":[92],"learning,":[95],"integrating":[96],"real-time":[97],"data":[98,130,150],"from":[99],"IMU":[101],"as":[102,160],"ground":[103],"truth.":[104],"The":[105,185],"second":[106],"utilizes":[108],"updated":[110],"solely":[118],"with":[119],"wristband.":[121],"In":[122],"other":[123],"words,":[124],"training":[126],"completed":[128],"during":[129],"acquisition,":[131],"allowing":[132],"trained":[134],"be":[137],"used":[138],"subsequent":[140],"estimation.":[142],"method":[144],"offers":[145],"advantages":[146],"adapting":[148],"drift":[151],"caused":[152],"by":[153],"variations":[154],"testing":[157],"configurations,":[158],"such":[159],"left":[162],"right":[164],"wrists":[165],"same":[168,177],"subject,":[169],"deviations":[170],"wearing":[173],"position":[174],"wrist,":[178],"even":[180],"differences":[181],"among":[182],"various":[183],"subjects.":[184],"results":[186],"indicate":[187],"that":[188],"exhibit":[191],"good":[192],"performance":[193],"under":[194],"strain":[195],"variations,":[196],"trajectory":[201],"proposed":[205],"has":[207],"approximate":[209],"error":[210],"15":[212],"degree":[213],"scenarios.":[216]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-30T00:00:00"}