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Automating Human Sleep Staging Analysis from Polysomnographic Recordings with a Discrete Hidden Markov Predictive Model

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Sleep-Staging-Analysis

Automating Human Sleep Staging Analysis from Polysomnographic Recordings with a Discrete Hidden Markov Predictive Model

Data

Go to https://www.physionet.org/content/sleep-edfx/1.0.0/ and download the polysomnographic data files.

Running

executemodel.py must be run with two arguments. The first argument to the program must the name of an individual data file (named with PSG.edf) and the second must be the corresponding annotations file with the same file name (named with Hypnogram.edf).

Requirements

This model requires the following modules:

  • numpy
  • sklearn
  • pyedflib

Troubleshooting

  • For certain data files, the model will run into an error such as not being able to read the annotations file or having a state sequence error.

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Automating Human Sleep Staging Analysis from Polysomnographic Recordings with a Discrete Hidden Markov Predictive Model

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