Comments (3)
GillesVandewiele
commented on June 12, 2024
It seems that the Lyapunov exponents are missing from the raw_features.csv file. For this, the slow parameter of FeaturesJager has to be set to true. It can take over 24 hours to extract the features for all 300 signals then though...
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gykovacs
commented on June 12, 2024
I think we can replace Lyapunov with Higushi, it should change much.
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GillesVandewiele
commented on June 12, 2024
I still have the old output which contains the lyapunov exponents... Perhaps we could merge that into our raw_features file?
EDIT: It also contains the Correlation dimension which is used in #29
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Related Issues (20)
- Hoseinzadeh, S., Amirani, M.C.: Use of electro hysterogram (ehg) signal to diagnose preterm birth. HOT 1
- Author list HOT 2
- Public datasets
- A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups HOT 3
- Create feature files HOT 2
- Consider general timeseries feature extraction packages (HCTSA & TSFRESH) HOT 2
- Create notebook/script to analyse the predictive power of features
- Scope of the present work HOT 1
- FeaturesSadiAhmed: KeyError HOT 2
- Fergus et al. "Prediction of preterm deliveries from EHG signals using machine learning" HOT 1
- Jager et al. "Characterization and automatic classification of preterm and term uterine records" HOT 3
- Ahmed et al. "A multivariate multiscale fuzzy entropy algorithm with application to uterine EMG complexity analysis" HOT 1
- Hussian et al. "Dynamic neural network architecture inspired by the immune algorithm to predict preterm deliveries in pregnant women" HOT 1
- Idowu et al. "Artificial Intelligence for detecting preterm uterine activity in gynecology and obstetric care"
- Fergus et al. "Advanced artificial neural network classification for detecting preterm births using EHG records" HOT 4
- Ren et al. "Improved prediction of preterm delivery using empirical mode decomposition analysis of uterine electromyography signals" HOT 1
- Acharya et al. "Automated detection of premature delivery using empirical mode and wavelet packet decomposition techniques with uterine electromyogram signals" HOT 6
- Hoseinzadeh et al. "Use of Electro Hysterogram (EHG) Signal to Diagnose Preterm Birth" HOT 11
- [NEW] Peng et al. "Evaluation of electrohysterogram measured from different gestational weeks for recognizing preterm delivery: a preliminary study using random Forest"
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