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SleepDetection

File descriptions (ipynb):

  • Merge_PA_SleepScores.ipynb: merges raw accelerometer data with sleep scores.
  • featureGeneration.ipynb: based on merged_data generated features for 30 second epochs and stores features, targets and timestamps in separate h5 files.
  • Merge_ArousalScores.ipynb: updates the target data (obtained through featureGeneration.ipynb) to also include arousal labels. Saves the new target values as a h5 file.
  • supervisedLearningMethods.ipynb: trains and tests binary sleep/wake decision tree, random forest and XGBoost classifiers using data from featureGeneration.ipynb.
  • arousalClassification.ipynb: trains and tests multiclass sleep/wake/arousal decision tree, random forest and XGBoost classifiers using data from featureGeneration.ipynb.
  • coMultiview.ipynb: trains and tests a co-training with multi-view method for binary sleep/wake classification.
  • coSingleview.ipynb: trains and tests a co-training with single-view method for binary sleep/wake classification.
  • supervisedMultiview.ipynb: trains and tests a supervised multi-view method for binary sleep/wake classification.
  • supervisedMultiviewClustering.ipynb: trains and tests a supervised multi-view with clustering method for binary sleep/wake classification.

Data format:

  • Raw accelerometer data: should include x-, y-, and z-values with timestamps from two tri-axial accelerometer sensors. Should be stored as a h5 file in a sequence based on timestamps.