{"id":"https://openalex.org/W3143349924","doi":"https://doi.org/10.1109/icm46511.2021.9385618","title":"Skeleton-based visualization of poor body movements in a child's gross-motor assessment using convolutional auto-encoder","display_name":"Skeleton-based visualization of poor body movements in a child's gross-motor assessment using convolutional auto-encoder","publication_year":2021,"publication_date":"2021-03-07","ids":{"openalex":"https://openalex.org/W3143349924","doi":"https://doi.org/10.1109/icm46511.2021.9385618","mag":"3143349924"},"language":"en","primary_location":{"id":"doi:10.1109/icm46511.2021.9385618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icm46511.2021.9385618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Mechatronics (ICM)","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/A5103055800","display_name":"Satoshi Suzuki","orcid":"https://orcid.org/0000-0003-1341-2808"},"institutions":[{"id":"https://openalex.org/I165522056","display_name":"Tokyo Denki University","ror":"https://ror.org/01pa62v70","country_code":"JP","type":"education","lineage":["https://openalex.org/I165522056"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Satoshi Suzuki","raw_affiliation_strings":["Graduate School of Advanced Science and Technology, Tokyo Denki University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Science and Technology, Tokyo Denki University, Tokyo, Japan","institution_ids":["https://openalex.org/I165522056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103831358","display_name":"Yukie Amemiya","orcid":null},"institutions":[{"id":"https://openalex.org/I158759429","display_name":"Japan Women's College of Physical Education","ror":"https://ror.org/01njgag08","country_code":"JP","type":"education","lineage":["https://openalex.org/I158759429"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yukie Amemiya","raw_affiliation_strings":["Faculty of Sports and Health Science, Japan Women's College of Physical Education, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sports and Health Science, Japan Women's College of Physical Education, Tokyo, Japan","institution_ids":["https://openalex.org/I158759429"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112513897","display_name":"Maiko Sato","orcid":null},"institutions":[{"id":"https://openalex.org/I158759429","display_name":"Japan Women's College of Physical Education","ror":"https://ror.org/01njgag08","country_code":"JP","type":"education","lineage":["https://openalex.org/I158759429"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Maiko Sato","raw_affiliation_strings":["Faculty of Sports and Health Science, Japan Women's College of Physical Education, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sports and Health Science, Japan Women's College of Physical Education, Tokyo, Japan","institution_ids":["https://openalex.org/I158759429"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103055800"],"corresponding_institution_ids":["https://openalex.org/I165522056"],"apc_list":null,"apc_paid":null,"fwci":0.5764,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.67120915,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9994000196456909,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9993000030517578,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/visualization","display_name":"Visualization","score":0.838335394859314},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.769447386264801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6061587929725647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5774813890457153},{"id":"https://openalex.org/keywords/gross-motor-skill","display_name":"Gross motor skill","score":0.5293107032775879},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5118505358695984},{"id":"https://openalex.org/keywords/movement-assessment","display_name":"Movement assessment","score":0.4477599859237671},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.44712504744529724},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.34382396936416626},{"id":"https://openalex.org/keywords/motor-skill","display_name":"Motor skill","score":0.3386877775192261},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3279293179512024},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18713226914405823},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15796518325805664},{"id":"https://openalex.org/keywords/developmental-psychology","display_name":"Developmental psychology","score":0.08940523862838745}],"concepts":[{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.838335394859314},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.769447386264801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6061587929725647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5774813890457153},{"id":"https://openalex.org/C114735433","wikidata":"https://www.wikidata.org/wiki/Q5610504","display_name":"Gross motor skill","level":3,"score":0.5293107032775879},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5118505358695984},{"id":"https://openalex.org/C2779106727","wikidata":"https://www.wikidata.org/wiki/Q22907079","display_name":"Movement assessment","level":3,"score":0.4477599859237671},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.44712504744529724},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34382396936416626},{"id":"https://openalex.org/C169976356","wikidata":"https://www.wikidata.org/wiki/Q13208902","display_name":"Motor skill","level":2,"score":0.3386877775192261},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3279293179512024},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18713226914405823},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15796518325805664},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","level":1,"score":0.08940523862838745},{"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/icm46511.2021.9385618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icm46511.2021.9385618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Mechatronics (ICM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.6399999856948853,"display_name":"No poverty"}],"awards":[{"id":"https://openalex.org/G1917245158","display_name":null,"funder_award_id":"JP18K11444,JP18K02764","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1959608418","https://openalex.org/W2031461964","https://openalex.org/W2031502857","https://openalex.org/W2047102387","https://openalex.org/W2053401092","https://openalex.org/W2071524685","https://openalex.org/W2082832830","https://openalex.org/W2107357190","https://openalex.org/W2136800805","https://openalex.org/W2156303437","https://openalex.org/W2271838665","https://openalex.org/W2476501661","https://openalex.org/W2559085405","https://openalex.org/W2573851627","https://openalex.org/W2747141180","https://openalex.org/W2897764506","https://openalex.org/W2907018078","https://openalex.org/W2911085338","https://openalex.org/W2912258320","https://openalex.org/W2943835771","https://openalex.org/W2946450932","https://openalex.org/W2962734576","https://openalex.org/W2974827766","https://openalex.org/W2996745432","https://openalex.org/W3011884980","https://openalex.org/W3043711813","https://openalex.org/W3100201746","https://openalex.org/W6662516092"],"related_works":["https://openalex.org/W4382176560","https://openalex.org/W3036697914","https://openalex.org/W3008125917","https://openalex.org/W2091882691","https://openalex.org/W3011937018","https://openalex.org/W2494613786","https://openalex.org/W2134634350","https://openalex.org/W2166339224","https://openalex.org/W2039454629","https://openalex.org/W2267674989"],"abstract_inverted_index":{"This":[0],"paper":[1],"deals":[2],"with":[3,65,69,91,117],"human":[4,15,26],"activity":[5],"recognition":[6],"(AR),":[7],"which":[8,88],"is":[9,51,55,80,89],"the":[10,20,86,100,102,136,146,163,169,173],"basic":[11],"technology":[12],"for":[13,25,99],"understanding":[14],"behavior":[16],"and":[17,74,95,105,111],"movement":[18],"in":[19,78],"field":[21],"of":[22,121,130,135,176],"sensing":[23],"applications":[24],"support":[27],"systems.":[28],"Focusing":[29],"on":[30],"children's":[31,47],"gross":[32],"motor":[33],"(GM)":[34],"skills":[35],"as":[36,57,82],"an":[37,61,118],"AR":[38],"target,":[39],"a":[40,70],"new":[41,112],"visualization":[42,54,165],"method":[43,166],"to":[44,124,156],"point":[45],"out":[46,129],"poor":[48,75],"body":[49],"movements":[50,68],"presented.":[52],"The":[53],"achieved":[56],"anomaly":[58],"detection":[59],"by":[60,85,145],"autoencoder":[62],"(AE)":[63],"trained":[64],"good":[66],"GM":[67,79,137],"complete":[71],"rating":[72],"score,":[73],"limb":[76],"motion":[77],"detected":[81],"anomal":[83],"points":[84,170],"GM-AE":[87],"combined":[90],"authors'":[92],"previous":[93,103],"GM-AR":[94,113,147],"AE.":[96],"In":[97],"preparation":[98],"GM-AE,":[101],"dataset":[104],"data":[106],"augmentation":[107],"have":[108],"been":[109],"improved,":[110],"was":[114,160],"completely":[115],"realized":[116],"identification":[119],"accuracy":[120],"99.3":[122],"%":[123],"148":[125],"actual":[126],"assessment":[127,133,138],"patterns":[128],"200":[131],"theoretical":[132],"combinations":[134],"tool":[139],"TGMD-3.":[140,177],"Using":[141],"appropriate":[142],"preparations":[143],"proven":[144],"stage,":[148],"we":[149],"investigated":[150],"some":[151],"deep":[152],"learning":[153],"conditions":[154],"related":[155],"GM-AE.":[157],"Finally,":[158],"it":[159],"confirmed":[161],"that":[162,171],"presented":[164],"can":[167],"emphasize":[168],"match":[172],"evaluation":[174],"items":[175]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
