{"id":"https://openalex.org/W3134803854","doi":"https://doi.org/10.1109/ssd49366.2020.9364244","title":"Hand-Gesture-Based Touchless Exploration of Medical Images with Leap Motion Controller","display_name":"Hand-Gesture-Based Touchless Exploration of Medical Images with Leap Motion Controller","publication_year":2020,"publication_date":"2020-07-20","ids":{"openalex":"https://openalex.org/W3134803854","doi":"https://doi.org/10.1109/ssd49366.2020.9364244","mag":"3134803854"},"language":"en","primary_location":{"id":"doi:10.1109/ssd49366.2020.9364244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd49366.2020.9364244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 17th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","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/A5008709390","display_name":"Safa Ameur","orcid":"https://orcid.org/0000-0003-3343-5388"},"institutions":[{"id":"https://openalex.org/I8636806","display_name":"University of Sousse","ror":"https://ror.org/00dmpgj58","country_code":"TN","type":"education","lineage":["https://openalex.org/I8636806"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Safa Ameur","raw_affiliation_strings":["Universit\u00e9 de Sousse, Ecole Nationale d'Ing\u00e9nieurs de Sousse,Sousse,Tunisie,4023"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Sousse, Ecole Nationale d'Ing\u00e9nieurs de Sousse,Sousse,Tunisie,4023","institution_ids":["https://openalex.org/I8636806"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021942590","display_name":"Anouar Ben Khalifa","orcid":"https://orcid.org/0000-0002-9946-0829"},"institutions":[{"id":"https://openalex.org/I8636806","display_name":"University of Sousse","ror":"https://ror.org/00dmpgj58","country_code":"TN","type":"education","lineage":["https://openalex.org/I8636806"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Anouar Ben Khalifa","raw_affiliation_strings":["ENISo,Sousse,Tunisie,4023"],"affiliations":[{"raw_affiliation_string":"ENISo,Sousse,Tunisie,4023","institution_ids":["https://openalex.org/I8636806"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049022989","display_name":"Med Salim Bouhlel","orcid":"https://orcid.org/0000-0003-2952-3967"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]},{"id":"https://openalex.org/I4210111338","display_name":"Institut Sup\u00e9rieur de Biotechnologie de Sfax","ror":"https://ror.org/02smqg134","country_code":"TN","type":"education","lineage":["https://openalex.org/I4210111338"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Med Salim Bouhlel","raw_affiliation_strings":["Universit\u00e9 de Sfax, Institut sup\u00e9rieure de Biotechnologie de Sfax, SETIT-Research Unit of Sciences of Electronic, Technologies of Information and Telecommunication,Safx,Tunisie,3038"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Sfax, Institut sup\u00e9rieure de Biotechnologie de Sfax, SETIT-Research Unit of Sciences of Electronic, Technologies of Information and Telecommunication,Safx,Tunisie,3038","institution_ids":["https://openalex.org/I4210111338","https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008709390"],"corresponding_institution_ids":["https://openalex.org/I8636806"],"apc_list":null,"apc_paid":null,"fwci":2.1174,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.87258616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"11"},"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7624594569206238},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7100001573562622},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6973638534545898},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6966468095779419},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.6890449523925781},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6215536594390869},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6206527948379517},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.5973055958747864},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5964028239250183},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5737224817276001},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.561938464641571},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.5271023511886597},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5075032114982605},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.48054105043411255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4680585265159607},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.46399208903312683},{"id":"https://openalex.org/keywords/virtual-keyboard","display_name":"Virtual keyboard","score":0.41664111614227295},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19940772652626038}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7624594569206238},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7100001573562622},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6973638534545898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6966468095779419},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.6890449523925781},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6215536594390869},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6206527948379517},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.5973055958747864},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5964028239250183},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5737224817276001},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.561938464641571},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.5271023511886597},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5075032114982605},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.48054105043411255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4680585265159607},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.46399208903312683},{"id":"https://openalex.org/C2780367331","wikidata":"https://www.wikidata.org/wiki/Q861170","display_name":"Virtual keyboard","level":2,"score":0.41664111614227295},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19940772652626038},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssd49366.2020.9364244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd49366.2020.9364244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 17th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6000000238418579,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W168063749","https://openalex.org/W594399067","https://openalex.org/W938399823","https://openalex.org/W1480450040","https://openalex.org/W1896724907","https://openalex.org/W1990729232","https://openalex.org/W2004546419","https://openalex.org/W2031264894","https://openalex.org/W2039604658","https://openalex.org/W2044472968","https://openalex.org/W2053577555","https://openalex.org/W2059353807","https://openalex.org/W2070336673","https://openalex.org/W2105136937","https://openalex.org/W2133715026","https://openalex.org/W2143530665","https://openalex.org/W2184075236","https://openalex.org/W2253107759","https://openalex.org/W2294030757","https://openalex.org/W2339243810","https://openalex.org/W2402265228","https://openalex.org/W2555506591","https://openalex.org/W2621436911","https://openalex.org/W2623997639","https://openalex.org/W2791724282","https://openalex.org/W2792778978","https://openalex.org/W2795901753","https://openalex.org/W2886899719","https://openalex.org/W2905346541","https://openalex.org/W2919341498","https://openalex.org/W2920395019","https://openalex.org/W2943314885","https://openalex.org/W2959753758","https://openalex.org/W2966879630","https://openalex.org/W2972546487","https://openalex.org/W3003646123","https://openalex.org/W3051032203","https://openalex.org/W6661594932","https://openalex.org/W6691541595","https://openalex.org/W6697018172","https://openalex.org/W6782286981"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2011666252","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456"],"abstract_inverted_index":{"Hand":[0],"gesture":[1],"recognition":[2,157],"has":[3],"become":[4],"one":[5],"of":[6,11,29,37,42,165],"the":[7,27,35,40,49,109,113,116,119,122,124,129,140,144,155,163,171],"most":[8],"interesting":[9],"means":[10],"contactless":[12,151],"human-computer":[13],"interaction.":[14],"There":[15],"is":[16],"significant":[17],"importance":[18],"for":[19,33],"commanding":[20],"medical":[21,69,168],"images":[22,70,169],"during":[23],"surgical":[24],"procedures":[25],"by":[26],"mean":[28],"touchless":[30,73],"hand":[31,64,98],"gestures":[32,65],"reducing":[34],"time":[36],"surgery":[38],"and":[39,81,97,102,128,137,143],"risk":[41],"contamination.":[43],"In":[44],"this":[45],"work,":[46],"we":[47],"used":[48],"Leap":[50],"Motion":[51],"Controller":[52],"as":[53,108],"an":[54],"acquisition":[55],"device,":[56],"with":[57,91,167],"different":[58],"classification":[59],"methods,":[60],"to":[61,67,161],"recognize":[62],"11":[63],"dedicated":[66],"manipulating":[68],"through":[71],"a":[72,84,150],"graphical":[74],"user":[75],"interface.":[76],"This":[77],"framework":[78],"was":[79,135],"trained":[80],"tested":[82],"on":[83,154],"benchmark":[85],"dataset":[86],"called":[87],"LeapGestureDB.":[88],"We":[89,148],"worked":[90],"statistical":[92],"features":[93],"calculated":[94],"from":[95],"fingers":[96],"data,":[99],"then":[100],"normalized":[101],"fed":[103],"into":[104],"various":[105],"classifiers":[106],"such":[107],"support":[110],"vector":[111],"machine,":[112],"nearest":[114],"neighbor,":[115],"decision":[117],"tree,":[118],"random":[120],"forest,":[121],"AdaBoost,":[123],"linear":[125],"discriminant":[126],"analysis":[127],"multi-layer":[130],"perceptron.":[131],"The":[132],"highest":[133],"accuracy":[134],"91.73%":[136],"89.91%":[138],"using":[139],"cubic":[141],"SVM":[142],"multilayer":[145],"perceptron,":[146],"respectively.":[147],"developed":[149],"interface":[152],"based":[153],"best":[156],"rate":[158],"in":[159,170],"order":[160],"facilitate":[162],"way":[164],"interaction":[166],"operating":[172],"room.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
