PhysioToolkit is a large and growing library of software for physiologic signal processing and analysis, detection of physiologically significant events using both classical techniques and novel methods based on statistical physics and nonlinear dynamics, interactive display and characterization of signals, creation of new databases, simulation of physiologic and other signals, quantitative evaluation and comparison of analysis methods, and analysis of nonequilibrium and nonstationary processes. A unifying theme of the research projects that contribute software to PhysioToolkit is the extraction of “hidden” information from biomedical signals, information that may have diagnostic or prognostic value in medicine, or explanatory or predictive power in basic research. All PhysioToolkit software is available in source form under the GNU General Public License (GPL).

References in zbMATH (referenced in 149 articles )

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  1. Daoui, Achraf; Karmouni, Hicham; Sayyouri, Mhamed; Qjidaa, Hassan: Stable analysis of large-size signals and images by Racah’s discrete orthogonal moments (2022)
  2. Dietrich, Felix; Yair, Or; Mulayoff, Rotem; Talmon, Ronen; Kevrekidis, Ioannis G.: Spectral discovery of jointly smooth features for multimodal data (2022)
  3. Joloudari, Javad Hassannataj; Saadatfar, Hamid; GhasemiGol, Mohammad; Alizadehsani, Roohallah; Sani, Zahra Alizadeh; Hasanzadeh, Fereshteh; Hassannataj, Edris; Sharifrazi, Danial; Mansor, Zulkefli: FCM-DNN: diagnosing coronary artery disease by deep accuracy fuzzy C-means clustering model (2022)
  4. Shang, Du; Shang, Pengjian: A novel approach of dependence measure for complex signals (2022)
  5. Adrian Lamela, Itziar Fernandez, Yolanda Larriba, Alejandro Rodriguez, Cristina Rueda: FMM: An R Package for Modeling Rhythmic Patterns in Oscillatory Systems (2021) arXiv
  6. Andrade, Daniel; Okajima, Yuzuru: Adaptive covariate acquisition for minimizing total cost of classification (2021)
  7. Erkuş, Ekin Can; Purutçuoğlu, Vilda: Outlier detection and quasi-periodicity optimization algorithm: frequency domain based outlier detection (FOD) (2021)
  8. Gnutti, Alessandro; Guerrini, Fabrizio; Adami, Nicola; Migliorati, Pierangelo; Leonardi, Riccardo: A wavelet filter comparison on multiple datasets for signal compression and denoising (2021)
  9. Gu, Danlei; Mi, Yujia; Lin, Aijing: Application of time-delay multiscale symbolic phase compensated transfer entropy in analyzing cyclic alternating pattern (CAP) in sleep-related pathological data (2021)
  10. Guedri, Hichem; Bajahzar, Abdullah; Belmabrouk, Hafedh: ECG compression with Douglas-Peucker algorithm and fractal interpolation (2021)
  11. Hendryx, Emily P.; Rivière, Béatrice M.; Rusin, Craig G.: An extended DEIM algorithm for subset selection and class identification (2021)
  12. Huang, Min; Sun, Zhongkui; Donner, Reik V.; Zhang, Jie; Guan, Shuguang; Zou, Yong: Characterizing dynamical transitions by statistical complexity measures based on ordinal pattern transition networks (2021)
  13. Hussain, Lal; Aziz, Wajid; Khan, Ishtiaq Rasool; Alkinani, Monagi H.; Alowibdi, Jalal S.: Machine learning based congestive heart failure detection using feature importance ranking of multimodal features (2021)
  14. Jin, Xiangyu; An, Jie; Zhan, Bohua; Zhan, Naijun; Zhang, Miaomiao: Inferring switched nonlinear dynamical systems (2021)
  15. Kang, Huan; Zhang, Xiaofeng; Zhang, Guangbin: Phase permutation entropy : a complexity measure for nonlinear time series incorporating phase information (2021)
  16. Kendal, Wayne S.: The snap, crackle and pop of solar flares explained (2021)
  17. Li, Zhiwei; Qian, Xiang; Feng, Feng; Qu, Timing; Xia, Yousheng; Zhou, Wenmeng: A continuous variation of roughness scaling characteristics across fractal and non-fractal profiles (2021)
  18. Mateos, Diego M.; Gómez-Ramírez, Jaime; Rosso, Osvaldo A.: Using time causal quantifiers to characterize sleep stages (2021)
  19. Moghadam, Farangis Sajadi; Moridani, Mohammad Karimi; Jalilehvand, Yasaman: Analysis of heart rate dynamics based on nonlinear lagged returned map for sudden cardiac death prediction in cardiovascular patients (2021)
  20. Pasos Ruiz, Alejandro; Flynn, Michael; Large, James; Middlehurst, Matthew; Bagnall, Anthony: The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances (2021)

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