title: Signal analysis and classification methods for the calcium transient data of stem cell-derived cardiomyocytes.
abstract: Calcium cycling is crucial in the excitation-contraction coupling of cardiomyocytes, and therefore has a key role in cardiac functionality. Cardiac disorders and different drugs alter the calcium transients of cardiomyocytes and can cause serious dysfunction of the heart. New insights into this biochemical phenomena can be achieved by studying and analyzing calcium transients. Calcium transients of spontaneously beating human induced pluripotent stem cell-derived cardiomyocytes were recorded for a data set of 280 signals. Our objective was to develop and program procedures: (1) to automatically detect cycling peaks from signals and to classify the peaks of signals as either normal or abnormal, and (2) on the basis of the preceding peak detection results, to classify the entire signals into either a normal class or an abnormal class. We obtained a classification accuracy of approximately 80% compared to class decisions made separately by an experienced researcher, which is promising for the further development of an automatic classification approach. Automated classification software would be beneficial in the future for analyzing cardiomyocyte functionality on a large scale when screening for the adverse cardiac effects of new potential compounds, and also in future clinical applications.
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland. Electronic address: Martti.Juhola@sis.uta.fi.
authors.forename: Martti
authors.initials: M
authors.lastname: Juhola
authors.affiliation: BioMediTech and School of Medicine, University of Tampere, Tampere, Finland.
authors.forename: Kirsi
authors.initials: K
authors.lastname: Penttinen
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Henry
authors.initials: H
authors.lastname: Joutsijoki
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Kirsi
authors.initials: K
authors.lastname: Varpa
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Jyri
authors.initials: J
authors.lastname: Saarikoski
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Jyrki
authors.initials: J
authors.lastname: Rasku
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Harri
authors.initials: H
authors.lastname: Siirtola
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Kati
authors.initials: K
authors.lastname: Iltanen
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Jorma
authors.initials: J
authors.lastname: Laurikkala
authors.affiliation: School of Information Sciences, University of Tampere, Tampere, Finland.
authors.forename: Heikki
authors.initials: H
authors.lastname: Hyyrö
authors.affiliation: Department of Electronics and Communication Engineering, Tampere University of Technology, Tampere, Finland.
authors.forename: Jari
authors.initials: J
authors.lastname: Hyttinen
authors.affiliation: BioMediTech and School of Medicine, University of Tampere, Tampere, Finland; Heart Hospital, Tampere University Hospital, Tampere, Finland.
authors.forename: Katriina
authors.initials: K
authors.lastname: Aalto-Setälä
mesh_terms: D002118:Calcium / Q000378:metabolism; D020013:Calcium Signaling / Q000502:physiology*; D006801:Humans; D057026:Induced Pluripotent Stem Cells / Q000166:cytology / Q000378:metabolism*; D032383:Myocytes, Cardiac / Q000166:cytology / Q000378:metabolism*; D012815:Signal Processing, Computer-Assisted; D012984:Software
chemical_list: D002118:Calcium
keywords: Biomedical data analysis; Calcium cycling abnormalities; Cardiomyocytes; Human pluripotent stem cells