{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:49:55Z","timestamp":1785890995575,"version":"3.56.0"},"reference-count":33,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Signal Processing"],"published-print":{"date-parts":[[2027,1]]},"DOI":"10.1016\/j.sigpro.2026.110801","type":"journal-article","created":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T15:41:56Z","timestamp":1782574916000},"page":"110801","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["SplineOP: A dynamic programming knot selection algorithm for time-series compression with quadratic splines"],"prefix":"10.1016","volume":"250","author":[{"given":"Nicol\u00e1s Enrique","family":"Cecchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent","family":"Runge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8527-8161","authenticated-orcid":false,"given":"Charles","family":"Truong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4750-2265","authenticated-orcid":false,"given":"Laurent","family":"Oudre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.sigpro.2026.110801_bib0001","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1080\/23080477.2023.2258643","article-title":"Compressed sensing for ECG signal compression using DWT based sensing matrices","volume":"11","author":"Parkale","year":"2023","journal-title":"Smart Sci."},{"issue":"4","key":"10.1016\/j.sigpro.2026.110801_bib0002","doi-asserted-by":"crossref","first-page":"1104","DOI":"10.1109\/JBHI.2017.2765922","article-title":"S-EMG Signal compression in one-dimensional and two-dimensional approaches","volume":"22","author":"Trabuco","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"2","key":"10.1016\/j.sigpro.2026.110801_bib0003","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s00778-014-0368-8","article-title":"A time-series compression technique and its application to the smart grid","volume":"24","author":"Eichinger","year":"2015","journal-title":"VLDB J."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110801_bib0004","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3264903","article-title":"Sprintz: time series compression for the internet of things","volume":"2","author":"Blalock","year":"2018","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"issue":"1","key":"10.1016\/j.sigpro.2026.110801_bib0005","article-title":"Time series compression for IoT: a systematic literature review","volume":"2023","author":"de Oliveira","year":"2023","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"10.1016\/j.sigpro.2026.110801_bib0006","doi-asserted-by":"crossref","first-page":"41","DOI":"10.3389\/fcomp.2020.00041","article-title":"Physically inspired data compression and management for industrial data analytics","volume":"2","author":"Sabbagh","year":"2020","journal-title":"Front. Comput. Sci."},{"key":"10.1016\/j.sigpro.2026.110801_bib0007","doi-asserted-by":"crossref","first-page":"S827","DOI":"10.1016\/S0098-1354(98)00158-6","article-title":"A B-spline based method for data compression, process monitoring and diagnosis","volume":"22","author":"Vedam","year":"1998","journal-title":"Comput. Chem. Eng."},{"issue":"1","key":"10.1016\/j.sigpro.2026.110801_bib0008","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/S0165-1684(97)00037-6","article-title":"ECG Data compression by spline approximation","volume":"59","author":"Karczewicz","year":"1997","journal-title":"Signal Process."},{"issue":"10","key":"10.1016\/j.sigpro.2026.110801_bib0009","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3560814","article-title":"Time series compression survey","volume":"55","author":"Chiarot","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.sigpro.2026.110801_bib0010","series-title":"Foundations of Spline Theory: B-Splines, Spline Approximation, and Hierarchical Refinement","author":"Lyche","year":"2018"},{"issue":"1","key":"10.1016\/j.sigpro.2026.110801_bib0011","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/0021-9045(68)90026-9","article-title":"On uniform approximation by splines","volume":"1","author":"De Boor","year":"1968","journal-title":"J. Approx. Theory"},{"key":"10.1016\/j.sigpro.2026.110801_bib0012","series-title":"Spline Models for Observational Data","author":"Wahba","year":"1990"},{"issue":"6","key":"10.1016\/j.sigpro.2026.110801_bib0013","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1002\/wics.125","article-title":"Splines, knots, and penalties","volume":"2","author":"Eilers","year":"2010","journal-title":"WIREs Comput. Stat."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110801_bib0014","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1016\/S0096-3003(03)00179-6","article-title":"Least squares splines with free knots: global optimization approach","volume":"149","author":"Beliakov","year":"2004","journal-title":"Appl. Math. Computat."},{"issue":"2","key":"10.1016\/j.sigpro.2026.110801_bib0015","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1137\/0715022","article-title":"Approximation to Data by Splines with Free Knots","volume":"15","author":"Jupp","year":"1978","journal-title":"SIAM Journal on Numerical Analysis"},{"issue":"4","key":"10.1016\/j.sigpro.2026.110801_bib0016","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/00036817408839073","article-title":"Splines (with optimal knots) are better","volume":"3","author":"Burchard","year":"1974","journal-title":"Applicable Analysis"},{"issue":"3","key":"10.1016\/j.sigpro.2026.110801_bib0017","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0173857","article-title":"A direct method to solve optimal knots of B-spline curves: an application for non-uniform B-spline curves fitting","volume":"12","author":"Dung","year":"2017","journal-title":"PloS one"},{"issue":"3","key":"10.1016\/j.sigpro.2026.110801_bib0018","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.jkss.2008.01.003","article-title":"On knot placement for penalized spline regression","volume":"37","author":"Yao","year":"2008","journal-title":"J. Korean Stat. Soc."},{"issue":"5","key":"10.1016\/j.sigpro.2026.110801_bib0019","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1007\/BF02169154","article-title":"Smoothing by spline functions. II","volume":"16","author":"Reinsch","year":"1971","journal-title":"Numer. Math."},{"key":"10.1016\/j.sigpro.2026.110801_bib0020","unstructured":"C.R. Rojas, B. Wahlberg, On change point detection using the fused lasso method, (2014) arXiv preprint arXiv: 1401.5408."},{"issue":"6","key":"10.1016\/j.sigpro.2026.110801_bib0021","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.1287\/ijoc.2021.0313","article-title":"l0 trend filtering","volume":"35","author":"Wen","year":"2023","journal-title":"INFORMS J. Comput."},{"issue":"7","key":"10.1016\/j.sigpro.2026.110801_bib0022","doi-asserted-by":"crossref","first-page":"524","DOI":"10.3390\/bios12070524","article-title":"New ECG compression method for portable ECG monitoring system merged with binary convolutional auto-encoder and residual error compensation","volume":"12","author":"Shi","year":"2022","journal-title":"Biosensors"},{"key":"10.1016\/j.sigpro.2026.110801_bib0023","unstructured":"D. Hsu, Time series compression based on adaptive piecewise recurrent autoencoder, (2017) arXiv preprint arXiv: 1707.07961."},{"key":"10.1016\/j.sigpro.2026.110801_bib0024","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v101.i10","article-title":"Generalized functional pruning optimal partitioning (GFPOP) for constrained changepoint detection in genomic data","volume":"101","author":"Hocking","year":"2022","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.sigpro.2026.110801_bib0025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v106.i06","article-title":"gfpop: an R package for univariate graph-constrained change-point detection","volume":"106","author":"Runge","year":"2023","journal-title":"J. Stat. Softw."},{"issue":"2","key":"10.1016\/j.sigpro.2026.110801_bib0026","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1080\/10618600.2018.1512868","article-title":"Detecting changes in slope with an L0 penalty","volume":"28","author":"Fearnhead","year":"2019","journal-title":"J. Comput. Graph. Stat."},{"key":"10.1016\/j.sigpro.2026.110801_bib0027","unstructured":"V. Runge, M. Pascucci, N.D. de Boishebert, Change-in-slope optimal partitioning algorithm in a finite-size parameter space, (2020) arXiv preprint arXiv: 2012.11573."},{"issue":"500","key":"10.1016\/j.sigpro.2026.110801_bib0028","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1080\/01621459.2012.737745","article-title":"Optimal detection of changepoints with a linear computational cost","volume":"107","author":"Killick","year":"2012","journal-title":"J. Am. Stat. Assoc."},{"issue":"2","key":"10.1016\/j.sigpro.2026.110801_bib0029","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1007\/s11222-016-9636-3","article-title":"On optimal multiple changepoint algorithms for large data","volume":"27","author":"Maidstone","year":"2017","journal-title":"Stat. Comput."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110801_bib0030","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1093\/biomet\/77.3.521","article-title":"Asymptotically optimal difference-based estimation of variance in nonparametric regression","volume":"77","author":"Hall","year":"1990","journal-title":"Biometrika"},{"issue":"2","key":"10.1016\/j.sigpro.2026.110801_bib0031","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1137\/070690274","article-title":"\\ell_1 trend filtering","volume":"51","author":"Kim","year":"2009","journal-title":"SIAM Rev."},{"key":"10.1016\/j.sigpro.2026.110801_bib0032","series-title":"Proceedings of the 33rd European Signal Processing Conference","first-page":"2687","article-title":"SPOP: time series compression with quadratic splines","author":"Cecchi","year":"2025"},{"key":"10.1016\/j.sigpro.2026.110801_bib0033","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5201\/ipol.2024.494","article-title":"Arm-CODA: a data set of upper-limb human movement during routine examination","volume":"14","author":"Combettes","year":"2024","journal-title":"Image Process. Line"}],"container-title":["Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165168426003142?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165168426003142?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:12:03Z","timestamp":1785888723000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0165168426003142"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,1]]},"references-count":33,"alternative-id":["S0165168426003142"],"URL":"https:\/\/doi.org\/10.1016\/j.sigpro.2026.110801","relation":{},"ISSN":["0165-1684"],"issn-type":[{"value":"0165-1684","type":"print"}],"subject":[],"published":{"date-parts":[[2027,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"SplineOP: A dynamic programming knot selection algorithm for time-series compression with quadratic splines","name":"articletitle","label":"Article Title"},{"value":"Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.sigpro.2026.110801","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110801"}}