{"id":"https://openalex.org/W2172300616","doi":"https://doi.org/10.1109/iros.2009.5354008","title":"A DCT-Gaussian classification scheme for human-robot interface","display_name":"A DCT-Gaussian classification scheme for human-robot interface","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W2172300616","doi":"https://doi.org/10.1109/iros.2009.5354008","mag":"2172300616"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2009.5354008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2009.5354008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086661051","display_name":"Srinivas Kota","orcid":"https://orcid.org/0000-0001-7870-4903"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srinivas Kota","raw_affiliation_strings":["Southem Illinois University, Carbondale, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southem Illinois University, Carbondale, IL, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045934367","display_name":"Michael Mace","orcid":"https://orcid.org/0000-0001-9599-448X"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Michael Mace","raw_affiliation_strings":["Department of Mechanical Engineering, University of Bristol, Bristol, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Bristol, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101588240","display_name":"Lalit Gupta","orcid":"https://orcid.org/0000-0003-1013-3221"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lalit Gupta","raw_affiliation_strings":["Southem Illinois University, Carbondale, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southem Illinois University, Carbondale, IL, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043916064","display_name":"Ravi Vaidyanathan","orcid":"https://orcid.org/0000-0002-9625-4544"},"institutions":[{"id":"https://openalex.org/I35364215","display_name":"Naval Postgraduate School","ror":"https://ror.org/033yfkj90","country_code":"US","type":"education","lineage":["https://openalex.org/I1330347796","https://openalex.org/I3130687028","https://openalex.org/I35364215"]},{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Ravi Vaidyanathan","raw_affiliation_strings":["Department of Mechanical Engineering, University of Bristol, Bristol, UK","US Naval Postgraduate School, Monterrey, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Bristol, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]},{"raw_affiliation_string":"US Naval Postgraduate School, Monterrey, CA, USA","institution_ids":["https://openalex.org/I35364215"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2176,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4779387,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"5503","last_page":"5508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9933000206947327,"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":0.9933000206947327,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9861999750137329,"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/T10860","display_name":"Speech and Audio Processing","score":0.9704999923706055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.8003221750259399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.696350634098053},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6397402286529541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6195232272148132},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5490843653678894},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.5143595933914185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5062893629074097},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4922908842563629},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.45910218358039856},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4578503668308258},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4309678375720978},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.41551342606544495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41191089153289795}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.8003221750259399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.696350634098053},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6397402286529541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6195232272148132},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5490843653678894},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.5143595933914185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5062893629074097},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4922908842563629},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.45910218358039856},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4578503668308258},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4309678375720978},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.41551342606544495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41191089153289795},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros.2009.5354008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2009.5354008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/d958549b-4e42-48db-a24c-116e324d562c","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/d958549b-4e42-48db-a24c-116e324d562c","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kota, S, Mace, MAV, Gupta, L & Vaidyanathan, R 2009, A DCT-gaussian classification scheme for human robot interface. in IEEE International Conference on Intelligent Robots and Systems (IROS), St Louis, MO, USA. pp. 5503 - 5508.","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4512864557","display_name":null,"funder_award_id":"EP/F01869X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1506281249","https://openalex.org/W1762207595","https://openalex.org/W1998677760","https://openalex.org/W2021148355","https://openalex.org/W2029333966","https://openalex.org/W2040378481","https://openalex.org/W2089762504","https://openalex.org/W2094728353","https://openalex.org/W2112987103","https://openalex.org/W2115105887","https://openalex.org/W2133332910","https://openalex.org/W2134130385","https://openalex.org/W2142197234","https://openalex.org/W2145164178","https://openalex.org/W2164006146","https://openalex.org/W2799061466","https://openalex.org/W4239875977","https://openalex.org/W6673941533"],"related_works":["https://openalex.org/W2055682261","https://openalex.org/W1916685473","https://openalex.org/W1993363272","https://openalex.org/W2174937762","https://openalex.org/W2186390138","https://openalex.org/W2790129917","https://openalex.org/W2060035984","https://openalex.org/W4311388919","https://openalex.org/W2169866437","https://openalex.org/W1964286703"],"abstract_inverted_index":{"The":[0,32,51,81],"ultimate":[1],"success":[2],"of":[3,46,66,69,83,105,151,182],"a":[4,24,63,121,147,179],"human-robot-interface":[5],"system":[6],"depends":[7],"on":[8,36],"how":[9],"accurately":[10,27],"user":[11],"control":[12,30,104,133],"signals":[13,98,153,184],"are":[14],"classified.":[15],"This":[16],"paper":[17,139],"is":[18,35,54,90,126],"aimed":[19],"at":[20],"developing":[21],"and":[22],"testing":[23],"strategy":[25,89],"to":[26,145,156,190],"classify":[28],"human-robot":[29],"signals.":[31],"primary":[33],"focus":[34],"overcoming":[37],"the":[38,44,70,76,84,114,127,130,158,162],"dimensionality":[39,52,159],"problem":[40,53],"frequently":[41],"encountered":[42],"in":[43,120,137,154],"design":[45],"Gaussian":[47,131],"multivariate":[48,132],"signal":[49,72,87,134],"classifiers.":[50],"overcome":[55],"by":[56,75,92],"selecting,":[57],"using":[58],"two":[59],"different":[60],"ranking":[61],"criteria,":[62],"small":[64],"set":[65],"linear":[67],"combinations":[68],"input":[71],"space":[73],"generated":[74],"discrete":[77],"cosine":[78],"transform":[79],"(DCT).":[80],"application":[82],"resulting":[85],"DCT-Gaussian":[86,115],"classification":[88,163],"demonstrated":[91],"classifying":[93],"tongue-movement":[94],"ear-pressure":[95],"(TMEP)":[96],"bioacoustic":[97],"that":[99,113,129],"have":[100],"been":[101],"proposed":[102],"for":[103,169,174],"an":[106],"assistive":[107,172],"robotic":[108],"arm.":[109],"Classification":[110],"results":[111],"show":[112],"classifiers":[116,118,135],"outperform":[117],"described":[119],"previous":[122],"study.":[123],"Most":[124],"noteworthy":[125],"fact":[128],"developed":[136],"this":[138],"can":[140,185],"be":[141,166,187],"designed":[142],"without":[143],"having":[144],"collect":[146],"prohibitively":[148],"large":[149],"number":[150,181],"training":[152,183],"order":[155],"satisfy":[157],"conditions.":[160],"Consequently,":[161],"strategies":[164],"will":[165],"especially":[167],"beneficial":[168],"designing":[170],"personalized":[171],"interfaces":[173],"individuals":[175],"from":[176],"whom":[177],"only":[178],"limited":[180],"reliably":[186],"collected":[188],"due":[189],"severe":[191],"disabilities.":[192]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}