{"id":"https://openalex.org/W3158406784","doi":"https://doi.org/10.1109/healthcom49281.2021.9399005","title":"TinyDL: Edge Computing and Deep Learning Based Real-time Hand Gesture Recognition Using Wearable Sensor","display_name":"TinyDL: Edge Computing and Deep Learning Based Real-time Hand Gesture Recognition Using Wearable Sensor","publication_year":2021,"publication_date":"2021-03-01","ids":{"openalex":"https://openalex.org/W3158406784","doi":"https://doi.org/10.1109/healthcom49281.2021.9399005","mag":"3158406784"},"language":"en","primary_location":{"id":"doi:10.1109/healthcom49281.2021.9399005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom49281.2021.9399005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on E-health Networking, Application &amp; Services (HEALTHCOM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5043599749","display_name":"Brian Coffen","orcid":null},"institutions":[{"id":"https://openalex.org/I161057412","display_name":"University of New Hampshire","ror":"https://ror.org/01rmh9n78","country_code":"US","type":"education","lineage":["https://openalex.org/I161057412"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Coffen","raw_affiliation_strings":["University of New Hampshire, Durham, NH, United Sttes"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Hampshire, Durham, NH, United Sttes","institution_ids":["https://openalex.org/I161057412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034911492","display_name":"Md Shaad Mahmud","orcid":"https://orcid.org/0000-0003-0454-565X"},"institutions":[{"id":"https://openalex.org/I161057412","display_name":"University of New Hampshire","ror":"https://ror.org/01rmh9n78","country_code":"US","type":"education","lineage":["https://openalex.org/I161057412"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md.Shaad Mahmud","raw_affiliation_strings":["University of New Hampshire, Durham, NH, United Sttes"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Hampshire, Durham, NH, United Sttes","institution_ids":["https://openalex.org/I161057412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161057412"],"apc_list":null,"apc_paid":null,"fwci":3.2458,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.94596493,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9995999932289124,"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":0.9995999932289124,"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/T11800","display_name":"User Authentication and Security Systems","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11446","display_name":"Mobile Health and mHealth Applications","score":0.9677000045776367,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"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/computer-science","display_name":"Computer science","score":0.8047615885734558},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.774388313293457},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.6910271644592285},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.6752723455429077},{"id":"https://openalex.org/keywords/bluetooth","display_name":"Bluetooth","score":0.5733970999717712},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5721614360809326},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5277004241943359},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49188661575317383},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.45672187209129333},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4552820920944214},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42551618814468384},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.42460185289382935},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.39934101700782776},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.38535165786743164},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3454306125640869},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09076544642448425}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8047615885734558},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.774388313293457},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.6910271644592285},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.6752723455429077},{"id":"https://openalex.org/C546215728","wikidata":"https://www.wikidata.org/wiki/Q39531","display_name":"Bluetooth","level":3,"score":0.5733970999717712},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5721614360809326},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5277004241943359},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49188661575317383},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.45672187209129333},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4552820920944214},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42551618814468384},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.42460185289382935},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.39934101700782776},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.38535165786743164},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3454306125640869},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09076544642448425},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/healthcom49281.2021.9399005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom49281.2021.9399005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on E-health Networking, Application &amp; Services (HEALTHCOM)","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":11,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2528906625","https://openalex.org/W2787495030","https://openalex.org/W2887324239","https://openalex.org/W2969825170","https://openalex.org/W2978495033","https://openalex.org/W3005641288","https://openalex.org/W3011785450","https://openalex.org/W3013003714","https://openalex.org/W3017361427","https://openalex.org/W3067862503"],"related_works":["https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W2010878661","https://openalex.org/W3147379364","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735","https://openalex.org/W3161179337"],"abstract_inverted_index":{"Offloading":[0],"data":[1,50,123],"analysis":[2,66,166],"to":[3,12,143,163,172],"edge":[4],"devices":[5,36],"by":[6],"decentralizing":[7],"processing":[8],"can":[9,18,29,57,74],"be":[10,30,58,75],"used":[11,37],"decrease":[13,19],"bandwidth":[14],"requirements,":[15],"latency,":[16],"and":[17,44,61,94,119,140,185],"the":[20,68,84,155,176,183,188],"total":[21],"transmission":[22],"time":[23,60],"required":[24],"in":[25,101,105],"wireless":[26,52,71],"devices.":[27,201],"This":[28],"especially":[31],"useful":[32],"for":[33,38,98,165,195],"compact":[34],"wearable":[35,69],"health":[39,196],"monitoring,":[40],"human":[41],"activity":[42],"recognition,":[43,46],"gesture":[45,108],"where":[47],"sending":[48],"raw":[49],"over":[51],"protocols":[53],"such":[54,102],"as":[55,199],"Bluetooth":[56],"both":[59],"power":[62,81],"consuming.":[63],"By":[64],"performing":[65],"on":[67,83,193],"device,":[70],"radio":[72],"usage":[73,100],"greatly":[76],"decreased,":[77],"reducing":[78],"a":[79,103,131,158],"main":[80],"consumer":[82],"device.":[85],"Deep":[86],"learning":[87],"(DL)":[88],"methods,":[89],"specifically":[90],"using":[91],"Tensorflow":[92],"(TF)":[93],"Keras":[95],"were":[96],"evaluated":[97,120],"their":[99],"case,":[104],"this":[106],"example":[107],"recognition.":[109],"A":[110],"multilayer":[111],"long":[112],"short-term":[113],"memory":[114],"(LSTM)":[115],"model":[116,156],"was":[117,141],"trained":[118],"off":[121],"of":[122,154,190],"(10":[124],"gestures,":[125],"1000":[126],"trials":[127],"total,":[128],"balanced)":[129],"from":[130,147],"finger-worn":[132],"ring":[133],"profile":[134],"device":[135],"that":[136],"collected":[137],"acceleration":[138],"data,":[139],"found":[142],"perform":[144],"with":[145],"accuracy":[146],"75-95%":[148],"per":[149],"gesture.":[150],"The":[151],"attempted":[152],"conversion":[153],"into":[157],"compressed":[159],"TF":[160],"Lite":[161],"format,":[162],"allow":[164],"on-device":[167],"did":[168],"not":[169],"succeed,":[170],"due":[171],"current":[173],"incompatibilities":[174],"between":[175],"different":[177],"frameworks.":[178],"Future":[179],"work":[180],"may":[181],"improve":[182],"accuracy,":[184],"potentially":[186],"expand":[187],"use":[189],"neural":[191],"networks":[192],"wearables":[194],"diagnostics":[197],"or":[198],"input":[200]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":2}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
