{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T03:41:35Z","timestamp":1793418095121,"version":"4.5.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T00:00:00Z","timestamp":1677456000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T00:00:00Z","timestamp":1677456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"e-Novia S.p.A."},{"DOI":"10.13039\/501100006690","name":"Politecnico di Milano","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006690","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cardiovasc Eng Tech"],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Breathing parameters change with activity and posture, but currently available solutions can perform measurements only during static conditions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This article presents an innovative wearable sensor system constituted by three inertial measurement units to simultaneously estimate respiratory rate (RR) in static and dynamic conditions and perform human activity recognition (HAR) with the same sensing principle. Two units are aimed at detecting chest wall breathing-related movements (one on the thorax, one on the abdomen); the third is on the lower back. All units compute the quaternions describing the subject\u2019s movement and send data continuously with the ANT transmission protocol to an app. The 20 healthy subjects involved in the research (9 men, 11 women) were between 23 and 54\u00a0years old, with mean age 26.8, mean height 172.5\u00a0cm and mean weight 66.9\u00a0kg. Data from these subjects during different postures or activities were collected and analyzed to extract RR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Statistically significant differences between dynamic activities (\u201cwalking slow\u201d, \u201cwalking fast\u201d, \u201crunning\u201d and \u201ccycling\u201d) and static postures were detected (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05), confirming the obtained measurements are in line with physiology even during dynamic activities. Data from the reference unit only and from all three units were used as inputs to artificial intelligence methods for HAR. When the data from the reference unit were used, the Gated Recurrent Unit was the best performing method (97% accuracy). With three units, a 1D Convolutional Neural Network was the best performing (99% accuracy).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\u00a0Overall, the proposed solution shows it is possible to perform simultaneous HAR and RR measurements in static and dynamic conditions with the same sensor system.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s13239-023-00657-3","type":"journal-article","created":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T13:02:52Z","timestamp":1677502972000},"page":"351-363","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["An IMU-Based Wearable System for Respiratory Rate Estimation in Static and Dynamic Conditions"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8266-9346","authenticated-orcid":false,"given":"Alessandra","family":"Angelucci","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Aliverti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"key":"657_CR1","doi-asserted-by":"publisher","first-page":"e27","DOI":"10.1183\/20734735.008417","volume":"13","author":"A Aliverti","year":"2017","unstructured":"Aliverti, A. Wearable technology: role in respiratory health and disease. Breathe. 13:e27\u2013e36, 2017.","journal-title":"Breathe"},{"key":"657_CR2","unstructured":"Aliverti, A., and A. Cesareo. A wearable device for the continuous monitoring of the respiratory rate. 2020."},{"key":"657_CR3","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1114\/1.1332084","volume":"29","author":"A Aliverti","year":"2001","unstructured":"Aliverti, A., R. Dellac\u00e0, P. Pelosi, D. Chiumello, L. Gattinoni, and A. Pedotti. Compartmental analysis of breathing in the supine and prone positions by optoelectronic plethysmography. Ann. Biomed. Eng. 29:60\u201370, 2001.","journal-title":"Ann. Biomed. Eng."},{"key":"657_CR4","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/978-3-662-65064-6_10","volume-title":"The Running Athlete: A Comprehensive Overview of Running in Different Sports","author":"A Aliverti","year":"2022","unstructured":"Aliverti, A., M. Evangelisti, and A. Angelucci. Wearable tech for long-distance runners. In: The Running Athlete: A Comprehensive Overview of Running in Different Sports, edited by G. L. Canata, H. Jones, W. Krutsch, P. Thoreux, and A. Vascellari. Berlin: Springer, 2022, pp. 77\u201389."},{"key":"657_CR5","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.pulmoe.2019.11.006","volume":"26","author":"A Angelucci","year":"2020","unstructured":"Angelucci, A., and A. Aliverti. Telemonitoring systems for respiratory patients: technological aspects. Pulmonology. 26:221\u2013232, 2020.","journal-title":"Pulmonology"},{"key":"657_CR6","unstructured":"Angelucci, A., A. Aliverti, D. Froio, and F. Moro. Metodo per il monitoraggio della frequenza respiratoria di una persona. Patent: 102021000029204, 2021."},{"key":"657_CR7","doi-asserted-by":"publisher","DOI":"10.1109\/star53492.2022.9860001","author":"A Angelucci","year":"2022","unstructured":"Angelucci, A., F. Camuncoli, M. Galli, and A. Aliverti. A wearable system for respiratory signal filtering based on activity: a preliminary validation. IEEE Int. Workshop Sport. 2022. https:\/\/doi.org\/10.1109\/star53492.2022.9860001.","journal-title":"IEEE Int. Workshop Sport"},{"key":"657_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s21030814","volume":"21","author":"A Angelucci","year":"2021","unstructured":"Angelucci, A., M. Cavicchioli, I. A. Cintorrino, G. Lauricella, C. Rossi, S. Strati, and A. Aliverti. Smart textiles and sensorized garments for physiological monitoring: a review of available solutions and techniques. Sensors (Switzerland). 21:1\u201323, 2021.","journal-title":"Sensors (Switzerland)"},{"key":"657_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.3012621","author":"A Angelucci","year":"2020","unstructured":"Angelucci, A., D. Kuller, and A. Aliverti. A home telemedicine system for continuous respiratory monitoring. IEEE J. Biomed. Heal. Informatics. 2020. https:\/\/doi.org\/10.1109\/JBHI.2020.3012621.","journal-title":"IEEE J. Biomed. Heal. Informatics"},{"key":"657_CR10","first-page":"2130","volume":"56","author":"A Angelucci","year":"2020","unstructured":"Angelucci, A., D. Kuller, and A. Aliverti. Respiratory rate and tidal volume change with posture and activity during daily life. Eur. Respir. J. 56:2130, 2020.","journal-title":"Eur. Respir. J."},{"key":"657_CR11","doi-asserted-by":"crossref","unstructured":"Antonelli, A., D. Guilizzoni, A. Angelucci, G. Melloni, F. Mazza, A. Stanzi, M. Venturino, D. Kuller, and A. Aliverti. Comparison between the AirgoTM device and a metabolic cart during rest and exercise. Sensors 2020.","DOI":"10.3390\/s20143943"},{"key":"657_CR12","doi-asserted-by":"publisher","first-page":"5994","DOI":"10.3390\/s22165994","volume":"22","author":"S Bernasconi","year":"2022","unstructured":"Bernasconi, S., A. Angelucci, and A. Aliverti. A scoping review on wearable devices for environmental monitoring and their application for health and wellness. Sensors. 22:5994, 2022.","journal-title":"Sensors"},{"key":"657_CR13","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1109\/10.554760","volume":"44","author":"CVC Bouten","year":"1997","unstructured":"Bouten, C. V. C., K. T. M. Koekkoek, M. Verduin, R. Kodde, and J. D. Janssen. A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity. IEEE Trans. Biomed. Eng. 44:136\u2013147, 1997.","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"657_CR14","first-page":"4","volume":"189","author":"J Brooke","year":"1996","unstructured":"Brooke, J. SUS-A quick and dirty usability scale. Usability Eval. Ind. 189:4\u20137, 1996.","journal-title":"Usability Eval. Ind."},{"key":"657_CR15","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1007\/s11517-020-02125-9","volume":"58","author":"A Cesareo","year":"2020","unstructured":"Cesareo, A., E. Biffi, D. Cuesta-Frau, M. G. D\u2019Angelo, and A. Aliverti. A novel acquisition platform for long-term breathing frequency monitoring based on inertial measurement units. Med. Biol. Eng. Comput. 58:785\u2013804, 2020.","journal-title":"Med. Biol. Eng. Comput."},{"key":"657_CR16","doi-asserted-by":"publisher","unstructured":"Cesareo, A., S. Gandolfi, I. Pini, E. Biffi, G. Reni, and A. Aliverti. A novel, low cost, wearable contact-based device for breathing frequency monitoring. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS 2402\u20132405, 2017. https:\/\/doi.org\/10.1109\/EMBC.2017.8037340","DOI":"10.1109\/EMBC.2017.8037340"},{"key":"657_CR17","first-page":"1","volume":"19","author":"A Cesareo","year":"2019","unstructured":"Cesareo, A., Y. Previtali, E. Biffi, and A. Aliverti. Assessment of breathing parameters using an inertial measurement unit (IMU)-based system. Sensors (Switzerland). 19:1\u201324, 2019.","journal-title":"Sensors (Switzerland)"},{"key":"657_CR18","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.artmed.2012.09.003","volume":"56","author":"M Chan","year":"2012","unstructured":"Chan, M., D. Est\u00e8ve, J.-Y. Fourniols, C. Escriba, and E. Campo. Smart wearable systems: current status and future challenges. Artif. Intell. Med. 56:137\u2013156, 2012.","journal-title":"Artif. Intell. Med."},{"key":"657_CR19","doi-asserted-by":"crossref","unstructured":"Chu, M., T. Nguyen, V. Pandey, Y. Zhou, H. N. Pham, R. Bar-Yoseph, S. Radom-Aizik, R. Jain, D. M. Cooper, and M. Khine. Respiration rate and volume measurements using wearable strain sensors. NPJ Digit. Med. 2:1\u20139, 2019.","DOI":"10.1038\/s41746-019-0083-3"},{"key":"657_CR20","doi-asserted-by":"publisher","first-page":"6666","DOI":"10.3390\/s21196666","volume":"21","author":"M Contini","year":"2021","unstructured":"Contini, M., A. Angelucci, A. Aliverti, P. Gugliandolo, B. Pezzuto, G. Berna, S. Romani, C. C. Tedesco, and P. Agostoni. Comparison between PtCO2 and PaCO2 and derived parameters in heart failure patients during exercise: a preliminary study. Sensors. 21:6666, 2021.","journal-title":"Sensors"},{"key":"657_CR21","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1089\/tmj.2013.0248","volume":"20","author":"I Faria","year":"2014","unstructured":"Faria, I., C. Gaspar, M. Zamith, I. Matias, R. C. D. Neves, F. Rodrigues, and C. B\u00e1rbara. TELEMOLD project: oximetry and exercise telemonitoring to improve long-term oxygen therapy. Telemed. e-Health. 20:626\u2013632, 2014.","journal-title":"Telemed. e-Health"},{"key":"657_CR22","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1007\/BF02600071","volume":"8","author":"JF Fieselmann","year":"1993","unstructured":"Fieselmann, J. F., M. S. Hendryx, C. M. Helms, and D. S. Wakefield. Respiratory rate predicts cardiopulmonary arrest for internal medicine inpatients. J. Gen. Intern. Med. 8:354\u2013360, 1993.","journal-title":"J. Gen. Intern. Med."},{"issue":"1","key":"657_CR23","doi-asserted-by":"publisher","first-page":"42","DOI":"10.3390\/jcm8010042","volume":"8","author":"C G\u00e1lvez-Barr\u00f3n","year":"2019","unstructured":"G\u00e1lvez-Barr\u00f3n, C., F. Villar-\u00c1lvarez, J. Ribas, F. Formiga, D. Chivite, R. Boixeda, C. Iborra, and A. Rodr\u00edguez-Molinero. Effort oxygen saturation and effort heart rate to detect exacerbations of chronic obstructive pulmonary disease or congestive heart failure. J. Clin. Med. 8(1):42, 2019.","journal-title":"J. Clin. Med."},{"key":"657_CR24","first-page":"5","volume":"19","author":"U Gerhardt","year":"2018","unstructured":"Gerhardt, U., R. Breitschwerdt, and O. Thomas. mHealth engineering: a technology review. J. Inf. Technol. Theory Appl. 19:5, 2018.","journal-title":"J. Inf. Technol. Theory Appl."},{"key":"657_CR25","unstructured":"Kingma, D. P., and J. Ba. Adam: A method for stochastic optimization. arXiv1412.6980 , 2014."},{"key":"657_CR26","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2010.5665859","author":"K Kunze","year":"2010","unstructured":"Kunze, K., G. Bahle, P. Lukowicz, and K. Partridge. Can magnetic field sensors replace gyroscopes in wearable sensing applications? Proc. Int. Symp. Wearable Comput. ISWC. 2010. https:\/\/doi.org\/10.1109\/ISWC.2010.5665859.","journal-title":"Proc. Int. Symp. Wearable Comput. ISWC"},{"key":"657_CR27","doi-asserted-by":"publisher","first-page":"07TR01","DOI":"10.1088\/1361-6579\/ab299e","volume":"40","author":"H Liu","year":"2019","unstructured":"Liu, H., J. Allen, D. Zheng, and F. Chen. Recent development of respiratory rate measurement technologies. Physiol. Meas. 40:07TR01, 2019.","journal-title":"Physiol. Meas."},{"key":"657_CR28","doi-asserted-by":"crossref","unstructured":"Madgwick, S. O. H., A. J. L. Harrison, and R. Vaidyanathan. Estimation of IMU and MARG orientation using a gradient descent algorithm. IEEE Int. Conf. Rehabil. Robot. 2011.","DOI":"10.1109\/ICORR.2011.5975346"},{"key":"657_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/jbio.201700263","volume":"11","author":"C Massaroni","year":"2018","unstructured":"Massaroni, C., C. Venanzi, A. P. Silvatti, D. L. Presti, P. Saccomandi, D. Formica, F. Giurazza, M. A. Caponero, and E. Schena. Smart textile for respiratory monitoring and thoraco-abdominal motion pattern evaluation. J. Biophoton. 11:1\u201312, 2018.","journal-title":"J. Biophoton."},{"key":"657_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12984-015-0060-2","volume":"12","author":"F Mass\u00e9","year":"2015","unstructured":"Mass\u00e9, F., R. R. Gonzenbach, A. Arami, A. Paraschiv-Ionescu, A. R. Luft, and K. Aminian. Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients. J. Neuroeng. Rehabil. 12:1\u201315, 2015.","journal-title":"J. Neuroeng. Rehabil."},{"key":"657_CR31","doi-asserted-by":"publisher","first-page":"1208","DOI":"10.1038\/s41551-020-00640-6","volume":"4","author":"T Mishra","year":"2020","unstructured":"Mishra, T., M. Wang, A. A. Metwally, G. K. Bogu, A. W. Brooks, A. Bahmani, A. Alavi, A. Celli, E. Higgs, O. Dagan-Rosenfeld, B. Fay, S. Kirkpatrick, R. Kellogg, M. Gibson, T. Wang, E. M. Hunting, P. Mamic, A. B. Ganz, B. Rolnik, X. Li, and M. P. Snyder. Pre-symptomatic detection of COVID-19 from smartwatch data. Nat. Biomed. Eng. 4:1208\u20131220, 2020.","journal-title":"Nat. Biomed. Eng."},{"key":"657_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s18072144","volume":"18","author":"D Naranjo-Hern\u00e1ndez","year":"2018","unstructured":"Naranjo-Hern\u00e1ndez, D., A. Talaminos-Barroso, J. Reina-Tosina, L. M. Roa, G. Barbarov-Rostan, P. Cejudo-Ramos, E. M\u00e1rquez-Mart\u00edn, and F. Ortega-Ruiz. Smart vest for respiratory rate monitoring of copd patients based on non-contact capacitive sensing. Sensors (Switzerland). 18:1\u201324, 2018.","journal-title":"Sensors (Switzerland)"},{"key":"657_CR33","doi-asserted-by":"publisher","first-page":"922","DOI":"10.3389\/fphys.2017.00922","volume":"8","author":"A Nicol\u00f2","year":"2017","unstructured":"Nicol\u00f2, A., C. Massaroni, and L. Passfield. Respiratory frequency during exercise: the neglected physiological measure. Front. Physiol. 8:922, 2017.","journal-title":"Front. Physiol."},{"key":"657_CR34","doi-asserted-by":"publisher","first-page":"1883","DOI":"10.4249\/scholarpedia.1883","volume":"4","author":"LE Peterson","year":"2009","unstructured":"Peterson, L. E. K-nearest neighbor. Scholarpedia. 4:1883, 2009.","journal-title":"Scholarpedia"},{"key":"657_CR35","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2019.2963048","author":"W Qi","year":"2019","unstructured":"Qi, W., and A. Aliverti. A multimodal wearable system for continuous and real-time breathing pattern monitoring during daily activity. IEEE J. Biomed. Heal. Informatics. 2019. https:\/\/doi.org\/10.1109\/JBHI.2019.2963048.","journal-title":"IEEE J. Biomed. Heal. Informatics"},{"key":"657_CR36","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1038\/nbt0308-303","volume":"26","author":"M Ringn\u00e9r","year":"2008","unstructured":"Ringn\u00e9r, M. What is principal component analysis? Nat. Biotechnol. 26:303\u2013304, 2008.","journal-title":"Nat. Biotechnol."},{"key":"657_CR37","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.resp.2010.05.018","volume":"172","author":"M Romei","year":"2010","unstructured":"Romei, M., A. L. Mauro, M. G. D\u2019Angelo, A. C. Turconi, N. Bresolin, A. Pedotti, and A. Aliverti. Effects of gender and posture on thoraco-abdominal kinematics during quiet breathing in healthy adults. Respir. Physiol. Neurobiol. 172:184\u2013191, 2010.","journal-title":"Respir. Physiol. Neurobiol."},{"key":"657_CR38","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1152\/jappl.1989.66.1.410","volume":"66","author":"MA Sackner","year":"1989","unstructured":"Sackner, M. A., H. Watson, A. S. Belsito, D. Feinerman, M. Suarez, G. Gonzalez, F. Bizousky, and B. Krieger. Calibration of respiratory inductive plethysmograph during natural breathing. J. Appl. Physiol. 66:410\u2013420, 1989.","journal-title":"J. Appl. Physiol."},{"key":"657_CR39","first-page":"1","volume":"19","author":"SA Shah","year":"2017","unstructured":"Shah, S. A., C. Velardo, A. Farmer, and L. Tarassenko. Exacerbations in chronic obstructive pulmonary disease: identification and prediction using a digital health system. J. Med. Int. Res. 19:1\u201314, 2017.","journal-title":"J. Med. Int. Res."},{"key":"657_CR40","doi-asserted-by":"publisher","DOI":"10.1002\/9780470753866","volume-title":"Business Intelligence: Data Mining and Optimization for Decision Making","author":"C Vercellis","year":"2009","unstructured":"Vercellis, C. Business Intelligence: Data Mining and Optimization for Decision Making. New York: Wiley Online Library, 2009."},{"key":"657_CR41","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1139\/apnm-2015-0140","volume":"40","author":"R Villar","year":"2015","unstructured":"Villar, R., T. Beltrame, and R. L. Hughson. Validation of the Hexoskin Wearable Vest During Lying, Sitting, Standing, and Walking Activities. Appl. Physiol. Nutr. Metab. 40:1019\u20131024, 2015.","journal-title":"Appl. Physiol. Nutr. Metab."},{"key":"657_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.smhl.2019.100105","volume":"15","author":"J Whitlock","year":"2020","unstructured":"Whitlock, J., J. Sill, and S. Jain. A-spiro: towards continuous respiration monitoring. Smart Heal.15:100105, 2020.","journal-title":"Smart Heal."},{"key":"657_CR43","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/0169-7439(87)80084-9","volume":"2","author":"S Wold","year":"1987","unstructured":"Wold, S., K. Esbensen, and P. Geladi. Principal component analysis. Chemom. Intell. Lab. Syst. 2:37\u201352, 1987.","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"657_CR44","doi-asserted-by":"publisher","first-page":"638793","DOI":"10.3389\/fbioe.2020.638793","volume":"8","author":"M Zago","year":"2021","unstructured":"Zago, M., A. F. R. Kleiner, and P. A. Federolf. Editorial: machine learning approaches to human movement analysis. Front. Bioeng. Biotechnol. 8:638793, 2021.","journal-title":"Front. Bioeng. Biotechnol."}],"container-title":["Cardiovascular Engineering and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13239-023-00657-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13239-023-00657-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13239-023-00657-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T14:07:08Z","timestamp":1691590028000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13239-023-00657-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,27]]},"references-count":44,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["657"],"URL":"https:\/\/doi.org\/10.1007\/s13239-023-00657-3","relation":{},"ISSN":["1869-408X","1869-4098"],"issn-type":[{"value":"1869-408X","type":"print"},{"value":"1869-4098","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,27]]},"assertion":[{"value":"9 August 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 January 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 February 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}