Feature Extraction from Accelerometers for classification

1. What is feature extraction in classification?
2. What are common methods of feature extraction?
3. What are features of accelerometer?

What is feature extraction in classification?

Feature Extraction uses an object-based approach to classify imagery, where an object (also called segment) is a group of pixels with similar spectral, spatial, and/or texture attributes. Traditional classification methods are pixel-based, meaning that spectral information in each pixel is used to classify imagery.

What are common methods of feature extraction?

Autoencoders, wavelet scattering, and deep neural networks are commonly used to extract features and reduce dimensionality of the data.

What are features of accelerometer?

Accelerometer sensors have the ability to alter obtained physical acceleration from motion or gravity into a voltage output. Accelerometers are widely used to measure inert acceleration due to gravity, the low-frequency module of the acceleration and the dynamic acceleration due to animal movement [36].