{"id":"https://openalex.org/W2108502280","doi":"https://doi.org/10.1109/icassp.2009.4959624","title":"Quantifying morphology changes in time series data with skew","display_name":"Quantifying morphology changes in time series data with skew","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2108502280","doi":"https://doi.org/10.1109/icassp.2009.4959624","mag":"2108502280"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4959624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959624","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1721.1/62155","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058754027","display_name":"Phil Sung","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Phil Sung","raw_affiliation_strings":["Massachusetts Institute Of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103067445","display_name":"Zeeshan Syed","orcid":"https://orcid.org/0000-0003-3838-0398"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeeshan Syed","raw_affiliation_strings":["Massachusetts Institute Of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007282049","display_name":"John V. Guttag","orcid":"https://orcid.org/0000-0003-0992-0906"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Guttag","raw_affiliation_strings":["Massachusetts Institute Of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":0.9679,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.72002762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"477","last_page":"480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.989799976348877,"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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8493772745132446},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.8255095481872559},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7478499412536621},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6122494339942932},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5758258700370789},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5629432201385498},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5505877733230591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48793289065361023},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4875587821006775},{"id":"https://openalex.org/keywords/hausdorff-distance","display_name":"Hausdorff distance","score":0.434310644865036},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.43275880813598633},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4261501729488373},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3956325650215149},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21000272035598755},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09172630310058594}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8493772745132446},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.8255095481872559},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7478499412536621},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6122494339942932},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5758258700370789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5629432201385498},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5505877733230591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48793289065361023},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4875587821006775},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.434310644865036},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.43275880813598633},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4261501729488373},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3956325650215149},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21000272035598755},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09172630310058594},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2009.4959624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959624","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/62155","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/62155","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/62155","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/62155","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"},"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1491458120","https://openalex.org/W1983712387","https://openalex.org/W2055910046","https://openalex.org/W2125101937","https://openalex.org/W2129414889","https://openalex.org/W2153708898","https://openalex.org/W2160754664","https://openalex.org/W2162800060"],"related_works":["https://openalex.org/W2341338763","https://openalex.org/W2950183183","https://openalex.org/W2030799363","https://openalex.org/W2032415964","https://openalex.org/W2288425735","https://openalex.org/W2349923317","https://openalex.org/W2894081631","https://openalex.org/W2986063033","https://openalex.org/W2978114332","https://openalex.org/W2040439981"],"abstract_inverted_index":{"This":[0],"paper":[1],"examines":[2],"strategies":[3],"to":[4,77],"quantify":[5],"differences":[6],"in":[7,18,55],"the":[8,19,81,85],"morphology":[9,47],"of":[10,84],"time":[11,16,51],"series":[12,52],"while":[13],"accounting":[14],"for":[15,28],"skew":[17],"observed":[20],"data.":[21],"We":[22,71],"adapt":[23],"four":[24],"measures":[25],"originally":[26],"designed":[27],"signal":[29],"shape":[30],"comparison:":[31],"Dynamic":[32],"Time-Warping":[33],"(DTW),":[34],"Earth":[35],"Mover's":[36],"Distance":[37,40,44],"(EMD),":[38],"Frochet":[39],"(FD),":[41],"and":[42,58],"Hausdorff":[43],"(HD).":[45],"These":[46],"difference":[48],"metrics":[49],"on":[50,61,67,80],"are":[53],"compared":[54],"discriminative":[56],"power":[57],"noise":[59],"resistance":[60],"ECG":[62],"signals":[63],"as":[64,66],"well":[65],"a":[68],"synthetic":[69],"dataset.":[70],"use":[72],"data":[73],"from":[74],"our":[75],"experiments":[76],"shed":[78],"light":[79],"relative":[82],"strengths":[83],"methods.":[86]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}