API Documentation

Processing Pipeline

MyoVerse core functionality is based on the processing pipeline. The pipeline is a sequence of filters that are applied to data objects.

While pipelines can be used individually, they are most commonly used to create datasets for supervised learning.

The following modules are available for creating pipelines and datasets:

Data Types

MyoVerse offers a variety of datatypes for supervised learning used in different publications

• Data Types

Filters

MyoVerse offers a variety of models for supervised learning used in different publications from the n-squared lab @ FAU Erlangen-Nürnberg.

• Filters
  • Generic Filters
  • Temporal Filters
  • Spatial Filters
  • Base Filter Classes

Datasets

MyoVerse offers a standard dataset for supervised learning that was used in different publications from the n-squared lab @ FAU Erlangen-Nürnberg.

• Datasets
  • Supervised Dataset
  • Default Supervised Datasets
  • Loader

Models

MyoVerse offers a variety of models for supervised learning used in different publications from the n-squared lab @ FAU Erlangen-Nürnberg.

Note

Only V16 is supported. The older models are available only for reference and inspiration.

• Definitions
  • Online Capable Models
  • Offline Models