Key settings for training a robust model are the Feature Extraction options.
Neuton framework generates these features for each selected axis from the defined window.
For example, the Max feature for accelerometer_X returns the maximum reading within each window.
By default, Edge AI Lab is configured for the best accuracy and footprint tradeoff. For this use case, select the following features:
- Absolute Mean
- Average Magnitude Difference
- Max
- Mean
- Mean Absolute Deviation
- Min
- Percentage of signal over mean
- Percentage of signal over zero
- Root mean square
- Zero-crossing Rate
- Mean-crossing Rate
- Negative sigma crossing rate (setting 1)
- Percentage of signal over sigma (setting 1)
- Positive sigma crossing rate (setting 1)
- Root Difference Square
- Standard Deviation
For each of the six axes, 16 features will be extracted, resulting in a total of 96 features per sample.
Some features have additional settings (for example, Positive sigma crossing rate). To change feature settings, click the Edit icon and select the settings from the drop-down menu.