User:Jonasswa
From Robin
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== Experiments == | == Experiments == | ||
=== Experiment 1 === | === Experiment 1 === | ||
| - | One of the first regressors going form accelerometer data to ECG data | + | [[Fil:ECG_TO_ACC_random250.png|thumb|600px|One of the first regressors going form accelerometer data to ECG data. This dense regressor is predicting an ECG signal when provided an ACC signal. The data is re-sampled to 250 Hz to reduce training time.]] |
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| - | + | ||
=== Experiment 2 === | === Experiment 2 === | ||
=== Experiment 3 === | === Experiment 3 === | ||
Revision as of 10:38, 12 October 2018
Contents |
Master
Thesis Structure
- Introduction
- Background
- The Human Heart
- Deep Learning
- Time-Series Signals
- Classifiers And Regressors
- Signal Processing Theory
- Available Data
- Experiment 1: Domain Analysis
- Idea
- Data preparation
- Time feature independent data set
- Time feature dependent data set
- Implementation
- Results
- Experiment 2: Classifying Cardiac Heart Functions
- Idea
- Preparations
- Implementation
- Results
- Experiment 3: Image Classification
- Idea
- Preparations
- Implementation
- Results
- Relation To Previous Research
- Future Work
- Conclusion
Questions
Is it possible to use motion data to predict the condition of the human heart? If so, can Deep Learning be used, and is it effective?
Do we need an invasive method for classification (accelerometer), or is it sufficient with a non-invasive method (ECG)?
