{"id":"https://openalex.org/W3162370835","doi":"https://doi.org/10.1109/icce50685.2021.9427735","title":"Dynamic Workout Detection in Smart Watch Using Artificial Neural Network","display_name":"Dynamic Workout Detection in Smart Watch Using Artificial Neural Network","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3162370835","doi":"https://doi.org/10.1109/icce50685.2021.9427735","mag":"3162370835"},"language":"en","primary_location":{"id":"doi:10.1109/icce50685.2021.9427735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce50685.2021.9427735","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 Consumer Electronics (ICCE)","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/A5113923824","display_name":"Vidushi Chaudhary","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Vidushi Chaudhary","raw_affiliation_strings":["Samsung R&D Institute Noida, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Noida, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035191475","display_name":"Bharat Singh Hada","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bharat Singh Hada","raw_affiliation_strings":["Samsung R&D Institute Noida, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Noida, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005984422","display_name":"Anand Deshbhratar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anand Deshbhratar","raw_affiliation_strings":["Samsung R&D Institute Noida, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Noida, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082391408","display_name":"Rishi Kaushik","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rishi Kaushik","raw_affiliation_strings":["Samsung R&D Institute Noida, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Noida, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006570988","display_name":"Ankit Verma","orcid":"https://orcid.org/0000-0003-3715-8613"},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankit Verma","raw_affiliation_strings":["Samsung R&D Institute Noida, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Noida, India","institution_ids":["https://openalex.org/I4210139030"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5113923824"],"corresponding_institution_ids":["https://openalex.org/I4210139030"],"apc_list":null,"apc_paid":null,"fwci":0.0961,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36248366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"15","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9878000020980835,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9878000020980835,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9740999937057495,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9207000136375427,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/accelerometer","display_name":"Accelerometer","score":0.8143104314804077},{"id":"https://openalex.org/keywords/gyroscope","display_name":"Gyroscope","score":0.7245438098907471},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6765662431716919},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6728283762931824},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6067371964454651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.446809858083725},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42360541224479675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3439328372478485},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21689236164093018}],"concepts":[{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.8143104314804077},{"id":"https://openalex.org/C158488048","wikidata":"https://www.wikidata.org/wiki/Q483400","display_name":"Gyroscope","level":2,"score":0.7245438098907471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6765662431716919},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6728283762931824},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6067371964454651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.446809858083725},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42360541224479675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3439328372478485},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21689236164093018},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce50685.2021.9427735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce50685.2021.9427735","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 Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1551782597","https://openalex.org/W2095705004","https://openalex.org/W2804739511","https://openalex.org/W2805786000","https://openalex.org/W2958431144","https://openalex.org/W3044454104","https://openalex.org/W3044651858","https://openalex.org/W6674330103"],"related_works":["https://openalex.org/W2356006086","https://openalex.org/W2545168295","https://openalex.org/W2365897603","https://openalex.org/W4234814094","https://openalex.org/W2156308897","https://openalex.org/W4303613760","https://openalex.org/W2361871310","https://openalex.org/W2417246878","https://openalex.org/W1982154684","https://openalex.org/W4290466010"],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,172],"smart":[3,6,22],"technology":[4],"like":[5,51],"watches":[7,23],"make":[8],"it":[9],"easy":[10],"for":[11,84,146],"the":[12,35,63],"user":[13],"to":[14,72],"keep":[15],"track":[16],"of":[17,26,38,62,89,124,158,165],"their":[18],"daily":[19],"activities.":[20,33],"Nowadays,":[21],"are":[24],"capable":[25],"efficiently":[27],"monitoring":[28],"routine":[29],"exercises":[30],"and":[31,43,54,65,108,110,160],"sport":[32],"But":[34],"current":[36],"solution":[37],"Human":[39],"Activity":[40,45],"Recognition":[41,46],"(HAR)":[42],"Sports":[44],"(SAR)":[47],"uses":[48],"multiple":[49],"sensors":[50],"accelerometer,":[52],"gyroscope,":[53],"magnetometer,":[55],"which":[56],"is":[57,140],"battery":[58],"intensive.":[59],"Further":[60],"most":[61],"HAR":[64],"SAR":[66,85,100],"solutions":[67],"have":[68],"not":[69],"been":[70],"subjected":[71],"real":[73,147,173],"time":[74,148,174],"testing.":[75,149,175],"To":[76],"overcome":[77],"this":[78,98],"problem,":[79],"we":[80,112],"propose":[81],"a":[82,92,125],"method":[83,121,152],"by":[86],"making":[87],"use":[88,123],"data":[90],"from":[91],"single":[93],"sensor":[94],"namely":[95],"accelerometer.":[96],"In":[97],"work":[99],"covers":[101],"4":[102],"activities":[103],"(badminton,":[104],"table":[105],"tennis,":[106],"squash":[107],"football),":[109],"together":[111],"denote":[113],"them":[114],"as":[115],"Dynamic":[116],"Workout":[117],"(DW).":[118],"The":[119,138,150,167],"proposed":[120,151],"makes":[122],"light":[126],"weight":[127],"Artificial":[128],"Neural":[129],"Network":[130],"(ANN)":[131],"model":[132,139,168],"with":[133],"only":[134],"2301":[135],"trainable":[136],"parameters.":[137],"deployed":[141],"on":[142],"Samsung":[143],"Galaxy":[144],"Watch3":[145],"achieved":[153,169],"True":[154,161],"Positive":[155],"rate":[156],"(TPR)":[157],"89.5%":[159],"Negative":[162],"Rate":[163],"(TNR)":[164],"92.3%.":[166],"100%":[170],"accuracy":[171]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}