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Analysis of nonstationarities in fetal heart rate signal: inconsistency measures of baselines using acceleration/deceleration patterns., , , , , and . ISSPA (2), page 9-12. IEEE, (2003)0-7803-7946-2.Description, analysis, and classification of biomedical signals: a computational intelligence approach., and . Soft Comput., 17 (9): 1659-1671 (2013)Clustering in augmented space of granular constraints: A study in knowledge-based clustering., , and . Pattern Recognit. Lett., (2015)Multi-Channels Time-Domain-Constrained Fuzzy c -Regression Models., , and . CORES, volume 30 of Advances in Soft Computing, page 263-270. Springer, (2005)Identification of Fuzzy Rule-Based Models With Output Space Knowledge Guidance., , , , , and . IEEE Trans. Fuzzy Syst., 29 (11): 3504-3518 (2021)Measurement of Blood Flow in the Carotid Artery as one of the Elements of Assessing the Ability for Pilots in the Gravitational Force Conditions-Review of Available Solutions., , , , and . PCBBE, volume 746 of Lecture Notes in Networks and Systems, page 395-405. Springer, (2023)Monitoring changes of pulse wave velocity PWV in medical telemonitoring system based on a synchronized, dispersed sensor network SWBAN., , , , , , and . MIXDES, page 510-514. IEEE, (2016)The Prediction of Fetal Outcome by Applying Neural Network for Evaluation of CTG Records., , , , , and . Computer Recognition Systems 2, volume 45 of Advances in Soft Computing, Springer, (2008)Development of information granules of higher type and their applications to granular models of time series., , , and . Eng. Appl. Artif. Intell., (2018)Corrigendum to Ä characterization of electrocardiogram signals through optimal allocation of information granularity" Artif. Intell. Med. 54(2012) 125-134., and . Artif. Intell. Medicine, 64 (3): 227 (2015)