{"id":"https://openalex.org/W7134056672","doi":"https://doi.org/10.48550/arxiv.2603.05418","title":"The Spatial and Temporal Resolution of Motor Intention in Multi-Target Prediction","display_name":"The Spatial and Temporal Resolution of Motor Intention in Multi-Target Prediction","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134056672","doi":"https://doi.org/10.48550/arxiv.2603.05418"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.05418","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128274206","display_name":"Marie Dominique Schmidt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmidt, Marie Dominique","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5084075127","display_name":"Ioannis Iossifidis","orcid":"https://orcid.org/0000-0002-9876-4396"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Iossifidis, Ioannis","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18570722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.557699978351593,"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":0.557699978351593,"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/T10982","display_name":"Motor Control and Adaptation","score":0.20069999992847443,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.11760000139474869,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.5307999849319458},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.515999972820282},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5077999830245972},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.44929999113082886},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.4088999927043915},{"id":"https://openalex.org/keywords/motor-control","display_name":"Motor control","score":0.34540000557899475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3366999924182892},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.3260999917984009}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297000288963318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6051999926567078},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.5307999849319458},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.515999972820282},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4390000104904175},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.4088999927043915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36579999327659607},{"id":"https://openalex.org/C137813230","wikidata":"https://www.wikidata.org/wiki/Q2996165","display_name":"Motor control","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.29739999771118164},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.295199990272522},{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C40743351","wikidata":"https://www.wikidata.org/wiki/Q7002049","display_name":"Neural decoding","level":3,"score":0.2777000069618225},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.05418","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.05418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.05418","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"pmh:doi:10.48550/arxiv.2603.05418","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reaching":[0],"for":[1,21,178],"grasping,":[2],"and":[3,23,36,44,48,72,88,108,122,146,169,185],"manipulating":[4],"objects":[5],"are":[6],"essential":[7],"motor":[8,15,111,151,173,192],"functions":[9],"in":[10,76,113,181,188],"everyday":[11],"life.":[12],"Decoding":[13],"human":[14],"intentions":[16,31],"is":[17],"a":[18,62,93,138],"central":[19],"challenge":[20],"rehabilitation":[22,115,183],"assistive":[24],"technologies.":[25],"This":[26,162],"study":[27],"focuses":[28],"on":[29,166],"predicting":[30],"by":[32,134],"inferring":[33],"movement":[34,58],"direction":[35],"target":[37,89],"location":[38],"from":[39],"multichannel":[40],"electromyography":[41],"(EMG)":[42],"signals,":[43],"investigating":[45],"how":[46],"spatially":[47],"temporally":[49],"accurate":[50],"such":[51],"information":[52],"can":[53,153],"be":[54,154],"detected":[55],"relative":[56],"to":[57,78,102,191],"onset.":[59],"We":[60],"present":[61],"computational":[63,189],"pipeline":[64],"that":[65,150],"combines":[66],"data-driven":[67],"temporal":[68,147,168],"segmentation":[69],"with":[70,158],"classical":[71],"deep":[73],"learning":[74],"classifiers":[75],"order":[77],"analyse":[79],"EMG":[80,142],"data":[81],"recorded":[82],"during":[83],"the":[84,167,176],"planning,":[85],"early":[86],"execution,":[87],"contact":[90],"phases":[91],"of":[92,141,172],"delayed":[94],"reaching":[95],"task.":[96],"Early":[97],"intention":[98,152],"prediction":[99],"enables":[100],"devices":[101],"anticipate":[103],"user":[104],"actions,":[105],"improving":[106],"responsiveness":[107],"supporting":[109],"active":[110],"recovery":[112],"adaptive":[114,182],"systems.":[116],"Random":[117],"Forest":[118],"achieves":[119],"$80\\%$":[120],"accuracy":[121,127],"Convolutional":[123],"Neural":[124],"Network":[125],"$75\\%$":[126],"across":[128],"$25$":[129],"spatial":[130,170],"targets,":[131],"each":[132],"separated":[133],"$14^\\circ$":[135],"azimuth/altitude.":[136],"Furthermore,":[137],"systematic":[139],"evaluation":[140],"channels,":[143],"feature":[144],"sets,":[145],"windows":[148],"demonstrates":[149],"efficiently":[155],"decoded":[156],"even":[157],"drastically":[159],"reduced":[160],"data.":[161],"work":[163],"sheds":[164],"light":[165],"evolution":[171],"intention,":[174],"paving":[175],"way":[177],"anticipatory":[179],"control":[180],"systems":[184],"driving":[186],"advancements":[187],"approaches":[190],"neuroscience.":[193]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-07T00:00:00"}
