{"id":"https://openalex.org/W7204266366","doi":"https://doi.org/10.6084/m9.figshare.33326679","title":"Multimodal sEMG and Accelerometer Dataset for Silent Speech Recognition","display_name":"Multimodal sEMG and Accelerometer Dataset for Silent Speech Recognition","publication_year":2026,"publication_date":"2026-08-26","ids":{"openalex":"https://openalex.org/W7204266366","doi":"https://doi.org/10.6084/m9.figshare.33326679"},"language":"en","primary_location":{"id":"doi:10.6084/m9.figshare.33326679","doi":"https://doi.org/10.6084/m9.figshare.33326679","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.33326679","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"volume":null,"type":"dataset","is_traditional":false,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.6084/m9.figshare.33326679","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148257789","display_name":"Hyeseong Jeon","orcid":"https://orcid.org/0009-0006-8098-141X","observed_orcids":["https://orcid.org/0009-0006-8098-141X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyeseong Jeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014752136","display_name":"Jangjay Sohn","orcid":"https://orcid.org/0000-0001-6095-0831","observed_orcids":["https://orcid.org/0000-0001-6095-0831"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jangjay Sohn","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6095-0831","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148240805","display_name":"Sungmin Jung","orcid":"https://orcid.org/0009-0007-5478-3011","observed_orcids":["https://orcid.org/0009-0007-5478-3011"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sungmin Jung","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0007-5478-3011","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148395711","display_name":"Taehee Kim","orcid":"https://orcid.org/0009-0006-2166-9354","observed_orcids":["https://orcid.org/0009-0006-2166-9354"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taehee Kim","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0006-2166-9354","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018807391","display_name":"Chang\u2010Hwan Im","orcid":"https://orcid.org/0000-0003-3795-3318","observed_orcids":["https://orcid.org/0000-0003-3795-3318"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang-Hwan Im","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.7768999934196472,"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"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.7768999934196472,"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/T10860","display_name":"Speech and Audio Processing","score":0.10620000213384628,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10667","display_name":"Emotion and Mood Recognition","score":0.02969999983906746,"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/silent-speech-recognition","display_name":"silent speech recognition","score":0.9620000123977661},{"id":"https://openalex.org/keywords/surface-electromyography","display_name":"surface electromyography","score":0.9309999942779541},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"inertial measurement unit","score":0.921999990940094},{"id":"https://openalex.org/keywords/facial-muscle-activity","display_name":"facial muscle activity","score":0.7720000147819519},{"id":"https://openalex.org/keywords/neck-muscle-activity","display_name":"neck muscle activity","score":0.8040000200271606},{"id":"https://openalex.org/keywords/english-word","display_name":"English word","score":0.4790000021457672},{"id":"https://openalex.org/keywords/roll-pitch-and-yaw","display_name":"roll pitch yaw","score":0.4729999899864197},{"id":"https://openalex.org/keywords/bandpass-filtering","display_name":"bandpass filtering","score":0.6930000185966492},{"id":"https://openalex.org/keywords/data-preprocessing","display_name":"data preprocessing","score":0.3529999852180481},{"id":"https://openalex.org/keywords/esp32-s3","display_name":"ESP32-S3","score":0.7039999961853027}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6399000287055969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6015999913215637},{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.5877000093460083},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.5630999803543091},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.5285999774932861},{"id":"https://openalex.org/C2779337067","wikidata":"https://www.wikidata.org/wiki/Q4800961","display_name":"Articulation (sociology)","level":3,"score":0.4918999969959259},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4268999993801117},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4253000020980835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4041999876499176},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3294999897480011},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.32409998774528503},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C2778681526","wikidata":"https://www.wikidata.org/wiki/Q420647","display_name":"Electrooculography","level":3,"score":0.3122999966144562},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C2780905192","wikidata":"https://www.wikidata.org/wiki/Q2341604","display_name":"Facial muscles","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.25110000371932983},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.6084/m9.figshare.33326679","doi":"https://doi.org/10.6084/m9.figshare.33326679","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.33326679","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},{"id":"doi:10.6084/m9.figshare.33326679.v1","doi":"https://doi.org/10.6084/m9.figshare.33326679.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.33326679.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.6084/m9.figshare.33326679","doi":"https://doi.org/10.6084/m9.figshare.33326679","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.33326679","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7204223502","https://openalex.org/W2395817516","https://openalex.org/W7160715687","https://openalex.org/W7099168816","https://openalex.org/W2999578458","https://openalex.org/W7110587676","https://openalex.org/W2059169992","https://openalex.org/W2613422906","https://openalex.org/W4393807735","https://openalex.org/W7098131436"],"abstract_inverted_index":{"Dataset":[0],"OverviewThis":[1],"dataset":[2,22,48,101,394,466,480,817,877],"contains":[3,49,102,240,613,640,649,676,688,878],"surface":[4],"electromyography":[5],"(sEMG)":[6],"and":[7,28,57,92,105,112,120,139,167,215,230,245,253,280,356,440,595,773,831,867],"inertial":[8],"measurement":[9,247,264,704,722],"unit":[10],"(IMU)":[11],"recordings":[12,50,107,308,322,397,744,755,791,881],"collected":[13,819],"during":[14,458,748],"silent":[15,33,201,365,446,844,857],"articulation":[16,94,447,463],"of":[17,30,163,298,349,417,590,604,631,635,667,671,737,746,758,822],"100":[18,76,236,293,381,418],"English":[19],"words.":[20],"The":[21,83,115,218,720,734,750,804],"was":[23,95,204,456,818],"acquired":[24,149,233,299],"for":[25,97,108,287,386,609,813,833,856],"the":[26,176,213,258,295,319,331,353,363,396,412,445,449,585,591,598,614,650,689,753,759,762,766,770,786,823,860,873,880,883],"development":[27],"evaluation":[29],"a":[31,89,151,160,199,288,346,427,431,677,842],"multimodal":[32],"speech":[34,366,845],"interface":[35,846],"(SSI)":[36],"that":[37,847],"combines":[38],"electrical":[39],"muscle":[40,145,850],"activity":[41,851],"with":[42,143,852],"articulatory":[43,853],"motion":[44,203,854],"information.The":[45],"publicly":[46,875],"available":[47,457,876],"from":[51,133,180,242,380,882],"10":[52,884],"healthy":[53,865,885],"participants":[54,73,866],"(6":[55],"males":[56],"4":[58,99,629,665],"females;":[59],"24.6":[60],"\u00b1":[61],"2.50":[62],"years).":[63],"Each":[64],"participant":[65,404,413],"completed":[66,405],"five":[67,207,243,406,592],"recording":[68,239,290,407,451,593,691],"sessions.":[69,408],"During":[70],"each":[71,93,109,410,416,438,610,638,674],"session,":[72,111,411],"silently":[74,414],"articulated":[75,415],"words":[77,85,122,420,423],"commonly":[78],"used":[79,361],"in":[80,88,126,362,392,426,725,765,836],"daily":[81],"life.":[82],"target":[84,113,121,419,422,599],"were":[86,131,148,220,232,328,342,360,377,424,441,776,783,797,807],"presented":[87,425],"randomized":[90,428],"order,":[91,726],"recorded":[96,132,205],"approximately":[98,235,292,716],"s.The":[100],"both":[103,864],"sEMG":[104,169,177,605,616,645,652,682],"IMU":[106,238,300,389,690],"participant,":[110,586],"word.":[114],"correspondence":[116],"between":[117],"word":[118,858],"indices":[119],"is":[123,467,481],"provided":[124,391,608],"separately":[125],"Word_List.csv.Data":[127],"AcquisitionsEMGSurface":[128],"EMG":[129],"signals":[130,170,178,231,376,806],"six":[134,246,721],"electrodes":[135],"positioned":[136,211],"over":[137],"facial":[138,214],"neck":[140],"regions":[141],"associated":[142,320,364,767,839,861],"speech-related":[144],"activity.":[146],"Signals":[147],"using":[150,206,430],"BioSemi":[152],"ActiveTwo":[153],"system":[154],"(BioSemi":[155],"B.V.,":[156],"Amsterdam,":[157],"Netherlands)":[158],"at":[159,234,291],"sampling":[161],"rate":[162],"2,048":[164,181,626],"Hz.Both":[165],"raw":[166],"preprocessed":[168,651,681],"are":[171,607,699],"provided.The":[172],"preprocessing":[173,401],"applied":[174],"to":[175,183,188,198,226,330,344,371,383,399,443,471,693,785,799,810],"included:downsampling":[179],"Hz":[182,193,382,385,812],"512":[184,662],"Hz;60-Hz":[185],"notch":[186],"filtering":[187],"suppress":[189],"power-line":[190],"interference;":[191],"and20\u2013210":[192],"band-pass":[194],"filtering.Each":[195],"trial":[196,439],"corresponds":[197],"4-s":[200,289,450],"articulation.IMUArticulatory":[202],"MPU-9250":[208],"sensor":[209,262,702],"units":[210],"on":[212],"submental":[216],"regions.":[217],"sensors":[219,244,711],"connected":[221],"through":[222],"an":[223,227,462,641],"I2C":[224],"multiplexer":[225],"ESP32-S3":[228],"microcontroller,":[229],"Hz.Each":[237],"data":[241,256,459,646,683,698],"components:x,":[248],"y,":[249,276,355,729,772],"z,":[250,277,730],"roll,":[251,278,731],"pitch,":[252,279,732],"yaw.The":[254],"stored":[255],"have":[257],"following":[259],"dimensional":[260],"organization:":[261],"\u00d7":[263,266,622,643,658,679,703,706,712,715],"component":[265,272,705],"time":[267,316,351,373,620,632,656,668,707,718,738,760,802],"point":[268,283,621,657,708],"where:sensor":[269],"=":[270,273],"5;measurement":[271],"6":[274,644,680,713],"(x,":[275],"yaw);":[281],"andtime":[282],"\u2248":[284],"400":[285,315,326,333,340,350,372,717,781,788,795,801],"samples":[286,301,327,341,782,796],"Hz.Because":[294],"actual":[296],"number":[297,736],"could":[302],"vary":[303],"slightly":[304,337,742,792],"across":[305],"trials,":[306],"some":[307],"contain":[309,395,752],"more":[310,324],"or":[311],"fewer":[312,338],"than":[313,325,339,780,794],"exactly":[314],"points.":[317,803],"In":[318,409],"study,":[321,768],"containing":[323,336],"truncated":[329,784],"first":[332,787],"samples.":[334],"Recordings":[335,778],"interpolated":[343,798],"obtain":[345,800],"standardized":[347],"length":[348],"points.Only":[352],"x,":[354,728,771],"z":[357,774],"acceleration":[358],"components":[359,714,723,775],"recognition":[367],"study.":[368],"After":[369],"standardization":[370,757],"points,":[374],"these":[375,400],"further":[378],"downsampled":[379,809],"50":[384,811],"model":[387,814],"input.The":[388],"files":[390,606,751],"this":[393],"prior":[398],"procedures.Experimental":[402],"ProtocolEach":[403],"once.The":[421],"order":[429],"custom":[432],"graphical":[433],"user":[434],"interface.":[435],"Participants":[436],"initiated":[437],"instructed":[442],"complete":[444],"within":[448],"period.":[452],"A":[453],"retry":[454],"function":[455],"acquisition":[460],"when":[461],"error":[464],"occurred.The":[465],"therefore":[468],"organized":[469,482,700],"according":[470],"three":[472],"principal":[473],"levels:participant":[474],"\u2192":[475,477],"session":[476],"wordDirectory":[478],"StructureThe":[479],"as":[483,820],"follows:":[484],"{Dataset_root}/":[485],"\u2502":[486,489,492,495,496,499,500,501,504,505,506,509,510,511,514,515,516,519,520,521,524,525,528,529,532,533,536,537,540,541,542,545,548,549,552,553,556,557,560,563,566,569,572,575,578],"\u251c\u2500\u2500":[487,490,493,497,502,507,512,517,526,530,534,546,550,554,561,564,567,573],"Word_List.csv":[488],"S01/":[491],"EMG/":[494],"session_1/":[498,547],"raw_word1.mat":[503],"word1.mat":[508,551],"raw_word2.mat":[513],"word2.mat":[518,555],"\u2514\u2500\u2500":[522,538,543,558,570,576,579,581],"...":[523,559,577,582],"session_2/":[527,562],"session_3/":[531,565],"session_4/":[535,568],"session_5/":[539,571],"IMU/":[544],"S02/":[574],"S10/":[580],"S{participant_index}":[583],"identifies":[584,588,597],"session_{session_index}":[587],"one":[589,694],"sessions,":[594],"word{word_index}":[596],"word.EMG":[600],"File":[601,685],"DescriptionTwo":[602],"types":[603],"trial.raw_word{word_index}.matThis":[611],"file":[612,639,648,675,687],"original":[615,754],"recording.MATLAB":[617],"variable:save_data_rawData":[618],"dimensions:":[619,655],"channel":[623,659],"Sampling":[624,660],"rate:":[625,661],"HzRecording":[627,663],"duration:":[628,664],"sNumber":[630,666],"points:":[633,669],"8,192Number":[634],"channels:":[636,672],"6Thus,":[637,673],"8192":[642],"matrix.word{word_index}.matThis":[647],"signal.MATLAB":[653],"variable:save_dataData":[654],"2,048Number":[670],"2048":[678],"matrix.IMU":[684],"Descriptionword{word_index}.matThis":[686],"corresponding":[692],"target-word":[695],"trial.MATLAB":[696],"variable:save_dataThe":[697],"as:":[701],"with:":[709],"5":[710],"points":[719,739],"correspond,":[724],"to:":[727],"yaw":[733],"exact":[735],"may":[740],"differ":[741],"among":[743],"because":[745],"variations":[747],"acquisition.":[749],"without":[756],"dimension.For":[761],"analyses":[763],"reported":[764],"only":[769,879],"used.":[777],"longer":[779],"samples,":[789],"whereas":[790],"shorter":[793],"resulting":[805],"subsequently":[808],"input.Associated":[815],"StudyThe":[816],"part":[821],"study:\u201cHybrid":[824],"Silent":[825],"Speech":[826],"Interface":[827],"Integrating":[828],"Surface":[829],"Electromyography":[830],"Accelerometer":[832],"Enhanced":[834],"Accuracy":[835],"Clinical":[837],"Applications.\u201dThe":[838],"study":[840,862],"investigated":[841],"hybrid":[843],"integrates":[848],"sEMG-derived":[849],"information":[855],"recognition.Although":[859],"included":[863],"individuals":[868],"who":[869],"had":[870],"undergone":[871],"laryngectomy,":[872],"present":[874],"participants.":[886]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-08-27T00:00:00"}