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Applying Machine Learning Algorithms for Automatic Detection of Swallowing from Sound.

, , , , , , and . EMBC, page 2584-2588. IEEE, (2019)

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Improving heart rate estimation in preterm infants with bivariate point process analysis of heart rate and respiration., , , and . EMBC, page 920-923. IEEE, (2016)Uncovering statistical features of bradycardia severity in premature infants using a point process model., , , and . EMBC, page 5855-5858. IEEE, (2015)A point process model of respiratory dynamics in early physiological development., , and . EMBC, page 3804-3807. IEEE, (2011)Individualized apnea prediction in preterm infants using cardio-respiratory and movement signals., , , , , and . BSN, page 1-6. IEEE, (2013)Predicting Bradycardia in Preterm Infants Using Point Process Analysis of Heart Rate., , , and . IEEE Trans. Biomed. Eng., 64 (9): 2300-2308 (2017)Transforming artifact to signal: A wavelet-based algorithm for quantifying neonatal movement., , , and . EMBC, page 5466-5469. IEEE, (2014)Optimizing stimulus waveforms for electroceuticals., and . Biol. Cybern., 113 (1-2): 191-199 (2019)Using physiological signals to predict apnea in preterm infants., , , , , and . ACSCC, page 1098-1102. IEEE, (2011)Explaining Deep Classification of Time-Series Data with Learned Prototypes., , , and . KDH@IJCAI, volume 2429 of CEUR Workshop Proceedings, page 15-22. CEUR-WS.org, (2019)Automated movement detection reveals features of maturation in preterm infants., , , and . EMBC, page 600-603. IEEE, (2020)