Welcome! This is the repository for all lectures, assignments, and datasets for Week 2 of the BeaverWorks Medlytics course for 2021. The slides are provided here for easy reference, but will be presented in lecture format. You should fork this repository at the beginning of the week and work on your own copy when completing notebooks and challenge projects.
Datasets Used in this Repo:
Human Recognition Using Smartphone Software Dataset from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/human+activity+recognition+using+smartphones
- Contains Jupyter Notebook lessons where students will need to write their own code
- Contains Jupyter Notebook Solutions (will be uploaded after lesson notebooks are completed by students)
- Contains lesson notebooks (and solutions) on the SIR model, Time Series Exercises 1 and 2, Signal Processing, Fourier Transformations, Signal Cleanup, ML on Signals, ANNs on Signal Data Using Keras, Introduction to CNNs, and 1D Convolutional Nets on Signal Data.
- Contains the Week 2 Signal Processing Challenge. This challenge requires students to work with segments of signals from electroencephalography, electrooculography, electromyography, respiratory airflow, and electrocardiography. From these segments they must predict whether the patient was in an aroused (awake), in non-REM1, non-REM2, non-REM3, or REM state. Created by Brian Xia
Sleep data challenge from Massachusetts General Hospital’s (MGH), Computational Clinical Neurophysiology Laboratory (CCNL), and the Clinical Data Animation Laboratory (CDAC): https://www.physionet.org/physiobank/database/challenge/2018/