{"id":"https://openalex.org/W7155406475","doi":"https://doi.org/10.48550/arxiv.2604.20673","title":"Short-time, Wavelet-inspired Mouse Submovement Detection","display_name":"Short-time, Wavelet-inspired Mouse Submovement Detection","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155406475","doi":"https://doi.org/10.48550/arxiv.2604.20673"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.20673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.20673","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009666304","display_name":"Auejin Ham","orcid":"https://orcid.org/0000-0003-3145-5991"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ham, Auejin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055234428","display_name":"Ben Boudaoud","orcid":"https://orcid.org/0000-0003-4195-0793"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boudaoud, Ben","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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.32710000872612,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.32710000872612,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.17890000343322754,"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/T12290","display_name":"Human Motion and Animation","score":0.07429999858140945,"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/set","display_name":"Set (abstract data type)","score":0.506600022315979},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5034000277519226},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4077000021934509},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.37529999017715454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37049999833106995},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.35670000314712524},{"id":"https://openalex.org/keywords/motor-activity","display_name":"Motor activity","score":0.3240000009536743}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5874999761581421},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5446000099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5414000153541565},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.506600022315979},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5034000277519226},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4077000021934509},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C2985495968","wikidata":"https://www.wikidata.org/wiki/Q422453","display_name":"Motor activity","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.29030001163482666},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C137813230","wikidata":"https://www.wikidata.org/wiki/Q2996165","display_name":"Motor control","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.20673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.20673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"},"sustainable_development_goals":[{"score":0.7386451363563538,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Submovements":[0],"are":[1],"ballistic":[2],"components":[3],"of":[4,11,23,51,79,82,94,100,104,126],"human":[5],"motion":[6],"constituting":[7],"a":[8,52,69,84,120],"large":[9],"part":[10],"motor":[12,25,28],"interaction":[13],"and":[14,19,27,48,58,76,135,141,144],"arising":[15],"from":[16,61,119],"the":[17,35,43,92,136],"cyclical":[18],"overlapping":[20],"cognitive":[21],"processes":[22],"perception,":[24],"planning,":[26],"execution.":[29],"Extracting":[30],"submovements":[31,60],"is":[32],"challenging":[33],"as":[34],"motions":[36],"tend":[37],"to":[38,55,74,133],"overlap,":[39],"or":[40],"start":[41],"before":[42],"previous":[44],"ends.":[45],"We":[46,90,129],"propose":[47],"evaluate":[49],"use":[50],"wavelet-inspired":[53],"technique":[54],"accurately":[56],"locate":[57],"parameterize":[59],"one-dimensional":[62],"speed":[63],"time":[64],"series.":[65],"Our":[66],"method":[67,96,132],"employs":[68],"self-weighted":[70],"loss":[71],"refinement":[72],"step":[73],"identify":[75],"improve":[77],"regions":[78],"poor":[80],"quality":[81],"fit,":[83],"challenge":[85],"for":[86,112,146],"simpler":[87],"wavelet":[88],"transforms.":[89],"demonstrate":[91],"accuracy":[93],"our":[95,131],"by":[97],"presenting":[98],"analysis":[99],"~6,400":[101],"1-2s":[102],"trials":[103],"synthetic":[105],"egocentric":[106],"camera":[107],"(first-person":[108],"shooter)":[109],"aim":[110],"data":[111,124],"which":[113],"we":[114],"know":[115],"ground":[116],"truth,":[117],"modeled":[118],"similarly":[121],"sized":[122],"real":[123],"set":[125],"13":[127],"users.":[128],"compare":[130],"dual-threshold":[134],"persistence":[137],"1D":[138],"segmentation":[139],"techniques":[140],"note":[142],"challenges":[143],"opportunities":[145],"future":[147],"improvements.":[148]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-24T00:00:00"}