{"id":"https://openalex.org/W4366381586","doi":"https://doi.org/10.1145/3584376.3584588","title":"IMU Based Human Gestures Recognition using Deep Learning for Wearable Devices","display_name":"IMU Based Human Gestures Recognition using Deep Learning for Wearable Devices","publication_year":2022,"publication_date":"2022-12-16","ids":{"openalex":"https://openalex.org/W4366381586","doi":"https://doi.org/10.1145/3584376.3584588"},"language":"en","primary_location":{"id":"doi:10.1145/3584376.3584588","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3584376.3584588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence","raw_type":"proceedings-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/A5084746585","display_name":"Lin Fu","orcid":"https://orcid.org/0000-0002-6021-1200"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Lin Fu","raw_affiliation_strings":["School of Design Innovation, Victoria University of Wellington, New Zealand"],"affiliations":[{"raw_affiliation_string":"School of Design Innovation, Victoria University of Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084746585"],"corresponding_institution_ids":["https://openalex.org/I41156924"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16820832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1196","last_page":"1199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9973000288009644,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9936000108718872,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.8583624362945557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7999156713485718},{"id":"https://openalex.org/keywords/smartwatch","display_name":"Smartwatch","score":0.741727352142334},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.740871250629425},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.7231454849243164},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6942793726921082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6709328293800354},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.659450352191925},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.6573721766471863},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.5987975597381592},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.543891429901123},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4663732647895813},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4105831980705261},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35457277297973633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33896976709365845},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.10556209087371826}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8583624362945557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7999156713485718},{"id":"https://openalex.org/C29794715","wikidata":"https://www.wikidata.org/wiki/Q5362345","display_name":"Smartwatch","level":3,"score":0.741727352142334},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.740871250629425},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.7231454849243164},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6942793726921082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6709328293800354},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.659450352191925},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.6573721766471863},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.5987975597381592},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.543891429901123},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4663732647895813},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4105831980705261},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35457277297973633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33896976709365845},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.10556209087371826},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584376.3584588","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3584376.3584588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1980601381","https://openalex.org/W2001053555","https://openalex.org/W2068841257","https://openalex.org/W2164466702","https://openalex.org/W2748628104","https://openalex.org/W2898607715","https://openalex.org/W2980714463","https://openalex.org/W3005135132","https://openalex.org/W4206706211","https://openalex.org/W6645982770","https://openalex.org/W6788556936"],"related_works":["https://openalex.org/W3032336428","https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W4312416068","https://openalex.org/W3147379364","https://openalex.org/W2010878661","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,30,46,65,81,96,104,113,130,141],"emergence":[4],"of":[5,32,48,56,64,75],"wearable":[6,22,72],"devices,":[7],"such":[8],"as":[9],"smartwatches":[10],"and":[11,129],"smart":[12],"glasses.":[13],"Based":[14],"on":[15,43,80,126],"this,":[16],"human":[17,36,66,121],"gesture":[18,37],"recognition":[19,38],"(HGR)":[20],"for":[21],"devices":[23],"has":[24],"been":[25],"a":[26,108,127],"popular":[27],"topic":[28],"in":[29],"community":[31],"computer":[33],"vision.":[34],"Previous":[35],"approaches":[39],"are":[40,69,78],"mainly":[41],"based":[42,79],"statistical":[44],"methods,":[45],"breakthrough":[47],"deep":[49,87],"learning":[50,99],"enables":[51],"researchers":[52],"to":[53,61,116,140],"make":[54],"use":[55],"different":[57],"neural":[58,83],"network":[59],"architectures":[60],"learn":[62],"features":[63,88],"gestures":[67],"that":[68,111,134],"collected":[70],"from":[71,89,98],"devices.":[73],"Most":[74],"these":[76],"methods":[77],"convolutional":[82],"network,":[84],"which":[85],"extracts":[86],"local":[90],"manna.":[91],"However,":[92],"this":[93],"way":[94],"impedes":[95],"models":[97],"global":[100,118],"information.":[101],"To":[102],"solve":[103],"problem,":[105],"we":[106],"propose":[107],"novel":[109],"approach":[110],"leverages":[112],"attention":[114],"mechanism":[115],"capture":[117],"information":[119],"about":[120],"gestures.":[122],"We":[123],"conduct":[124],"experiments":[125],"benchmark,":[128],"experimental":[131],"results":[132],"demonstrate":[133],"our":[135],"proposed":[136],"method":[137],"is":[138],"superior":[139],"other":[142],"baselines.":[143]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
