{"id":"https://openalex.org/W2112021557","doi":"https://doi.org/10.1109/tim.2011.2135070","title":"A Novel Hierarchical Information Fusion Method for Three-Dimensional Upper Limb Motion Estimation","display_name":"A Novel Hierarchical Information Fusion Method for Three-Dimensional Upper Limb Motion Estimation","publication_year":2011,"publication_date":"2011-04-26","ids":{"openalex":"https://openalex.org/W2112021557","doi":"https://doi.org/10.1109/tim.2011.2135070","mag":"2112021557"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2011.2135070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2011.2135070","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050079548","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0003-0204-3867"},"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"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Zhi-Qiang Zhang","raw_affiliation_strings":["Department of Computing, Imperial College London, London, UK","Dept. of Comput., Imperial Coll. London, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Dept. of Comput., Imperial Coll. London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101839872","display_name":"Jiankang Wu","orcid":"https://orcid.org/0000-0003-2867-8676"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian-Kang Wu","raw_affiliation_strings":["Sensor Networks and Application Research Center, Chinese Academy of Sciences (CAS), Beijing, China","Sensor Networks & Applic. Res. Center, Grad. Univ. of the Chinese Acad. of Sci., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Sensor Networks and Application Research Center, Chinese Academy of Sciences (CAS), Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Sensor Networks & Applic. Res. Center, Grad. Univ. of the Chinese Acad. of Sci., Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050079548"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":157.3613,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.99907342,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"60","issue":"11","first_page":"3709","last_page":"3719"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11325","display_name":"Inertial Sensor and Navigation","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11325","display_name":"Inertial Sensor and Navigation","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12740","display_name":"Gait Recognition and Analysis","score":0.9943000078201294,"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":0.9934999942779541,"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/motion-capture","display_name":"Motion capture","score":0.7552163600921631},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6521570086479187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6208817958831787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5469744801521301},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5363135933876038},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.49898505210876465},{"id":"https://openalex.org/keywords/quaternion","display_name":"Quaternion","score":0.4859963357448578},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.48015159368515015},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.44820713996887207},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4430595636367798},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.43338537216186523},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.3294873833656311},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24439066648483276},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1336078643798828}],"concepts":[{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.7552163600921631},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6521570086479187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208817958831787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5469744801521301},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5363135933876038},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.49898505210876465},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.4859963357448578},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.48015159368515015},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.44820713996887207},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4430595636367798},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.43338537216186523},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3294873833656311},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24439066648483276},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1336078643798828},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2011.2135070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2011.2135070","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1215311137","https://openalex.org/W1527786550","https://openalex.org/W1975007458","https://openalex.org/W2020496717","https://openalex.org/W2040378481","https://openalex.org/W2040857266","https://openalex.org/W2050849695","https://openalex.org/W2102548030","https://openalex.org/W2108341823","https://openalex.org/W2110331760","https://openalex.org/W2110728483","https://openalex.org/W2116478510","https://openalex.org/W2120665422","https://openalex.org/W2135552275","https://openalex.org/W2152531733","https://openalex.org/W2155067987","https://openalex.org/W2160337655","https://openalex.org/W2161237417","https://openalex.org/W2169746842","https://openalex.org/W2171670888","https://openalex.org/W2172233963","https://openalex.org/W3139397654","https://openalex.org/W4229748564","https://openalex.org/W6628228489","https://openalex.org/W6663230341","https://openalex.org/W6680103918","https://openalex.org/W6685126934"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W3127350447","https://openalex.org/W3108700312","https://openalex.org/W2354322770","https://openalex.org/W4225472102","https://openalex.org/W2382948573","https://openalex.org/W4237547500","https://openalex.org/W2887325221","https://openalex.org/W3099445031","https://openalex.org/W2184550115"],"abstract_inverted_index":{"Motion":[0],"capture":[1,42,72],"provides":[2],"the":[3,7,15,23,59,82,94,107,136,151,156,177,181,198,206,209,216,222,231,240],"best":[4],"interface":[5],"to":[6,167,214,239],"understanding":[8],"of":[9,62,81,126,138,211],"trajectory":[10],"planning":[11],"and":[12,28,36,56,114,129,148,170,204,220],"formations":[13],"in":[14,25,50,84,98,142,185,201,208],"central":[16],"nervous":[17],"system,":[18],"which":[19,44,144,179],"has":[20,90],"enormously":[21],"benefited":[22],"research":[24,112],"interactive":[26],"game":[27],"learning,":[29],"animation,":[30],"film":[31],"special":[32],"effects,":[33],"health":[34],"care,":[35],"navigation.":[37],"The":[38,225],"existing":[39],"human":[40,70,99,130,158],"motion":[41,71,88,100,120,186],"techniques,":[43],"use":[45],"structured":[46],"multiple":[47],"high-resolution":[48],"cameras":[49],"a":[51,66,116,162,193],"dedicated":[52],"studio,":[53],"are":[54],"complicated":[55],"expensive.":[57],"With":[58],"rapid":[60],"development":[61],"microsensors":[63,77],"on":[64],"chip,":[65],"ubiquitous":[67],"real-time":[68],"low-cost":[69],"system":[73],"that":[74,230],"uses":[75],"wearable":[76],"becomes":[78],"possible.":[79],"Because":[80],"agility":[83],"movement,":[85],"upper":[86,108,118,139],"limb":[87,109,119,140],"estimation":[89,121,187,223],"been":[91],"regarded":[92],"as":[93,110],"most":[95,182],"difficult":[96],"problem":[97],"capture.":[101],"In":[102],"this":[103],"paper,":[104],"we":[105,191],"take":[106],"our":[111],"subject":[113],"present":[115,192],"novel":[117,194],"algorithm":[122,233],"by":[123,196],"hierarchical":[124],"fusion":[125,218],"sensor":[127,172,217],"data":[128],"skeleton":[131],"constraints.":[132],"Our":[133],"method":[134],"represents":[135],"orientations":[137],"segments":[141],"quaternion,":[143],"is":[145,165,180],"computationally":[146],"effective":[147],"can":[149,234],"avoid":[150],"singularity":[152],"problem.":[153],"To":[154,174],"address":[155],"nonlinear":[157],"body":[159],"segment":[160],"motion,":[161],"particle":[163,212],"filter":[164,213],"proposed":[166,232],"fuse":[168,205],"inertial":[169,189],"magnetic":[171],"data.":[173],"compensate":[175],"for":[176],"drift,":[178],"challenging":[183],"issue":[184],"using":[188],"sensors,":[190],"solution":[195],"modeling":[197],"geometrical":[199],"constraint":[200,207],"elbow":[202],"joint":[203],"framework":[210],"revise":[215],"results":[219,227,237],"improve":[221],"accuracy.":[224],"experimental":[226],"have":[228],"shown":[229],"provide":[235],"accurate":[236],"compared":[238],"ground":[241],"truth.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":3}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}