{"id":"https://openalex.org/W6908468670","doi":"https://doi.org/10.26190/unsworks/22069","title":"Developing Wearable Applications with Innovative Sensing Modalities for Human Activity Recognition and Key Generation","display_name":"Developing Wearable Applications with Innovative Sensing Modalities for Human Activity Recognition and Key Generation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W6908468670","doi":"https://doi.org/10.26190/unsworks/22069"},"language":"en","primary_location":{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/70086","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.4/70086","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"http://purl.org/coar/resource_type/c_db06"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.26190/unsworks/22069","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Lin, Qi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lin, Qi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"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":true,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.6047000288963318,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.6047000288963318,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.32030001282691956,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.007300000172108412,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6809999942779541},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.666700005531311},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6525999903678894},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5514000058174133},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4936000108718872},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.45339998602867126},{"id":"https://openalex.org/keywords/smartwatch","display_name":"Smartwatch","score":0.4487000107765198},{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"Photoplethysmogram","score":0.41589999198913574},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.40630000829696655}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6809999942779541},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.666700005531311},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6525999903678894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6144000291824341},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5514000058174133},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4936000108718872},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C29794715","wikidata":"https://www.wikidata.org/wiki/Q5362345","display_name":"Smartwatch","level":3,"score":0.4487000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44769999384880066},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.41589999198913574},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.40630000829696655},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.39169999957084656},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.38199999928474426},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3492000102996826},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3366999924182892},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29670000076293945},{"id":"https://openalex.org/C2779623668","wikidata":"https://www.wikidata.org/wiki/Q7652842","display_name":"SwIPe","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2793999910354614},{"id":"https://openalex.org/C176563091","wikidata":"https://www.wikidata.org/wiki/Q669238","display_name":"Intelligent sensor","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2776240099","wikidata":"https://www.wikidata.org/wiki/Q327018","display_name":"Interrogation","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25540000200271606},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C14103023","wikidata":"https://www.wikidata.org/wiki/Q11681459","display_name":"Pairing","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/70086","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.4/70086","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"http://purl.org/coar/resource_type/c_db06"},{"id":"doi:10.26190/unsworks/22069","is_oa":true,"landing_page_url":"https://doi.org/10.26190/unsworks/22069","pdf_url":null,"source":{"id":"https://openalex.org/S7407053176","display_name":"University of New South Wales","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"thesis"}],"best_oa_location":{"id":"doi:10.26190/unsworks/22069","is_oa":true,"landing_page_url":"https://doi.org/10.26190/unsworks/22069","pdf_url":null,"source":{"id":"https://openalex.org/S7407053176","display_name":"University of New South Wales","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"thesis"},"sustainable_development_goals":[{"score":0.9179873466491699,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Innovative":[0],"sensing":[1,21,41],"modalities":[2],"for":[3,161,174,263,304,330],"wearable":[4,177],"devices":[5,178,307],"continue":[6],"to":[7,19,44,55,106,113,151,201,259,289,299,323],"emerge":[8],"with":[9,34,92],"the":[10,86,114,128,146,191,210,254,301],"advancement":[11],"of":[12,63,74,88,130,213,232,247,256,311],"microelectromechanical":[13],"systems":[14],"and":[15,52,80,135,154,197,266,282],"material":[16],"science.":[17],"Compared":[18],"conventional":[20,203],"modalities,":[22,42],"these":[23,162],"are":[24,66],"either":[25],"more":[26,29],"accurate":[27],"or":[28,49,205],"energy":[30,50,316],"efficient.":[31],"In":[32,111,190],"keeping":[33],"this":[35,37,64],"trend,":[36],"thesis":[38,65],"introduces":[39],"innovative":[40],"aiming":[43],"quantitatively":[45],"improve":[46],"on":[47,229,273],"accuracy":[48],"consumption":[51,317],"finally":[53],"lead":[54],"qualitatively":[56],"difference":[57],"in":[58],"working":[59],"scenarios.":[60],"The":[61],"contributions":[62],"three-folded.":[67],"Firstly,":[68],"via":[69],"implementing":[70],"a":[71,99,122,131,136,172,181,219,243,279,309],"new":[72],"type":[73],"highly":[75,116],"sensitive,":[76],"stretchable,":[77],"optical":[78],"transparent,":[79],"low-cost":[81],"strain":[82,118],"sensor,":[83,119],"we":[84,120,167,194,216,252,276],"addressed":[85],"problem":[87],"human":[89,124],"posture":[90],"detection":[91,158],"casual":[93,109],"loose-fitting":[94],"smart":[95,100],"garments.":[96],"We":[97],"developed":[98,168,277],"garment":[101],"system\u2014E-Jacket\u2014by":[102],"attaching":[103],"novel":[104,115,220],"sensors":[105,200],"an":[107],"off-the-shelf":[108],"jacket.":[110],"addition":[112],"sensitive":[117],"implemented":[121,195],"state-of-the-art":[123],"activity":[125],"recognition":[126],"tool,":[127],"combination":[129],"convolutional":[132],"neural":[133],"network":[134],"long":[137],"short-term":[138],"memory":[139],"recurrent":[140],"network.":[141],"Our":[142,237,292],"evaluation":[143],"showed":[144,239,294],"that":[145,225,240,286,295],"E-Jacket":[147],"can":[148,226],"achieve":[149],"up":[150],"91.7,":[152],"84.4,":[153],"88.4":[155],"per":[156,249,320],"cent":[157],"accuracy,":[159],"respectively,":[160],"three":[163],"case":[164],"studies.":[165],"Second,":[166],"H2B,":[169],"which":[170,326],"is":[171,297],"system":[173,285],"securely":[175],"pairing":[176,244],"by":[179,318],"generating":[180],"shared":[182],"secret":[183,268],"key":[184,234,283,303],"from":[185],"interpulse":[186],"interval":[187],"between":[188],"heartbeats.":[189],"H2B":[192,241],"system,":[193],"cost-":[196],"energy-efficient":[198],"piezoelectric":[199],"replacing":[202],"electrocardiogram":[204],"photoplethysmogram":[206],"sensors.":[207],"To":[208],"handle":[209],"high":[211],"rate":[212,246],"bit":[214],"mismatch,":[215],"also":[217],"proposed":[218],"compressive":[221],"sensing-based":[222],"reconciliation":[223],"method":[224],"be":[227],"adopted":[228],"all":[230],"kinds":[231],"symmetric":[233,267],"generation":[235,270,284],"systems.":[236],"results":[238,293],"has":[242],"success":[245],"95.6":[248],"cent.":[250],"Third,":[251],"explored":[253],"feasibility":[255],"using":[257],"KEHs":[258],"collect":[260],"gait":[261],"signals":[262],"device":[264],"authentication":[265,281],"keys":[269],"continuously.":[271],"Based":[272],"preliminary":[274],"analysis,":[275],"KEHKey,":[278],"gait-based":[280],"uses":[287],"KEH":[288],"replace":[290],"accelerometers.":[291],"KEHKey":[296],"able":[298],"generate":[300],"same":[302],"two":[305],"KEH-embedded":[306],"at":[308],"speed":[310],"12.57":[312],"bps,":[313],"while":[314],"reducing":[315],"59":[319],"cent,":[321],"compared":[322],"accelerometer-based":[324],"methods,":[325],"makes":[327],"it":[328],"suitable":[329],"continuous":[331],"operation.":[332]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
