{"id":"https://openalex.org/W2783887164","doi":"https://doi.org/10.1109/cdc.2017.8264352","title":"Nonlinear dynamics of the human smooth pursuit system in health and disease: Model structure and parameter estimation","display_name":"Nonlinear dynamics of the human smooth pursuit system in health and disease: Model structure and parameter estimation","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783887164","doi":"https://doi.org/10.1109/cdc.2017.8264352","mag":"2783887164"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2017.8264352","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2017.8264352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 56th Annual Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-334957","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034670385","display_name":"Viktor Bro","orcid":"https://orcid.org/0000-0001-8754-3056"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Viktor Bro","raw_affiliation_strings":["Division of Systems and Control, Uppsala University, Uppsala, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of Systems and Control, Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043092463","display_name":"Alexander Medvedev","orcid":"https://orcid.org/0000-0002-6608-250X"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Alexander V. Medvedev","raw_affiliation_strings":["Division of Systems and Control, Uppsala University, Uppsala, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of Systems and Control, Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034670385"],"corresponding_institution_ids":["https://openalex.org/I123387679"],"apc_list":null,"apc_paid":null,"fwci":1.1293,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78565427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4692","last_page":"4697"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10250","display_name":"Glaucoma and retinal disorders","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10250","display_name":"Glaucoma and retinal disorders","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9835000038146973,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9757000207901001,"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/smooth-pursuit","display_name":"Smooth pursuit","score":0.6468243598937988},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6136528849601746},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5505417585372925},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.5226754546165466},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5025701522827148},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.49372920393943787},{"id":"https://openalex.org/keywords/eye-movement","display_name":"Eye movement","score":0.4861573874950409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45631536841392517},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4426670968532562},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4132468104362488},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3917485773563385},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3683539927005768},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32980579137802124},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.29622185230255127},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1460781991481781},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14312347769737244}],"concepts":[{"id":"https://openalex.org/C10324989","wikidata":"https://www.wikidata.org/wiki/Q3400677","display_name":"Smooth pursuit","level":3,"score":0.6468243598937988},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6136528849601746},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5505417585372925},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.5226754546165466},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5025701522827148},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.49372920393943787},{"id":"https://openalex.org/C153050134","wikidata":"https://www.wikidata.org/wiki/Q760256","display_name":"Eye movement","level":2,"score":0.4861573874950409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45631536841392517},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4426670968532562},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4132468104362488},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3917485773563385},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3683539927005768},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32980579137802124},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29622185230255127},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1460781991481781},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14312347769737244},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cdc.2017.8264352","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2017.8264352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 56th Annual Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:uu-334957","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-334957","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:uu-334957","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-334957","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W96573894","https://openalex.org/W1492026570","https://openalex.org/W1513008779","https://openalex.org/W1963603675","https://openalex.org/W1974718273","https://openalex.org/W1974907186","https://openalex.org/W1991951696","https://openalex.org/W2049500176","https://openalex.org/W2061171613","https://openalex.org/W2068196806","https://openalex.org/W2120677479","https://openalex.org/W2122512809","https://openalex.org/W2156408975","https://openalex.org/W2160337655","https://openalex.org/W2491178967","https://openalex.org/W2577807847","https://openalex.org/W2582627468","https://openalex.org/W2764122009","https://openalex.org/W4302415172","https://openalex.org/W4302798701"],"related_works":["https://openalex.org/W1905449104","https://openalex.org/W12665548","https://openalex.org/W2046329632","https://openalex.org/W2016692452","https://openalex.org/W2079137817","https://openalex.org/W2073929825","https://openalex.org/W1483178512","https://openalex.org/W1441246881","https://openalex.org/W1991346175","https://openalex.org/W2258563959"],"abstract_inverted_index":{"Oculomotor":[0],"tests":[1],"(OMT)":[2],"are":[3,21,39,70,128,145],"administered":[4],"to":[5,17,45,183],"quantify":[6],"symptoms":[7],"in":[8,15,42,53,68,178,186],"neurological":[9],"and":[10,29,61,112,118,185],"mental":[11],"diseases.":[12],"Eye":[13],"movements":[14],"response":[16],"displayed":[18],"visual":[19],"stimuli":[20],"registered":[22],"by":[23,90,147,163],"an":[24,105],"digital":[25],"video-based":[26],"eye":[27],"tracker":[28],"processed.":[30],"Stimuli":[31],"of":[32,49,82,92,122,134,142,158],"simple":[33],"signal":[34],"form,":[35],"e.g.":[36],"sine":[37],"waves,":[38],"traditionally":[40],"used":[41],"medical":[43],"practice":[44],"test":[46,75],"the":[47,50,62,66,74,80,84,116,131,135,139,143,153,156,159,164,173,176,179],"performance":[48,157],"oculomotor":[51],"system":[52,94],"smooth":[54],"pursuit":[55],"(SP).":[56],"The":[57],"calculated":[58],"SP":[59,85,180],"gain":[60],"phase":[63],"shift":[64],"at":[65],"frequency":[67,111],"question":[69],"then":[71],"presented":[72],"as":[73],"outcome.":[76],"This":[77],"paper":[78],"revisits":[79],"problem":[81],"quantifying":[83],"dynamics":[86,181],"from":[87,104,130],"eye-tracking":[88],"data":[89,170],"means":[91],"nonlinear":[93],"identification.":[95],"First,":[96],"a":[97,123,148],"sparse":[98,166],"Volterra-Laguerre":[99],"(VL)":[100],"model":[101,126,167],"is":[102,161],"estimated":[103],"OMT":[106],"with":[107],"sufficiently":[108],"exciting":[109],"(in":[110],"amplitude)":[113],"stimuli.":[114],"Then":[115],"structure":[117],"initial":[119],"parameter":[120,140],"estimates":[121,133],"polynomial":[124],"Wiener":[125],"(WM)":[127],"obtained":[129],"kernel":[132],"VL":[136],"model.":[137],"Finally,":[138],"distributions":[141],"WM":[144],"inferred":[146],"particle":[149],"filter":[150],"(PF).":[151],"In":[152],"proposed":[154],"approach,":[155],"PF":[160],"improved":[162],"individualized":[165],"structure.":[168],"Experimental":[169],"show":[171],"that":[172],"latter":[174],"captures":[175],"alternations":[177],"due":[182],"aging":[184],"Parkinson's":[187],"disease.":[188]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}