muscle_sense_net

MuscleSenseNet

muscle_sense_net is a machine learning model designed for predicting finger movements based on forearm muscle pressure points. This model is developed for the openmuscle.org project, which aims to advance research on forearm muscle-based finger sensors.

Overview

The muscle_sense_net model leverages data from custom sensors that measure pressure points on the forearm and real finger movements captured by the LASK system. The model uses a random forest regressor to make predictions based on the input data.

Features

Accurate prediction of finger movements using forearm muscle pressure points Integration with custom pressure point sensors and the LASK system Based on random forest regression for robust and interpretable predictions Installation To install the muscle_sense_net model, follow the instructions in the Hugging Face model repository.

Contributing

Contributions to muscle_sense_net are welcome. Please submit your pull requests or open an issue on the project's GitHub repository. For more information about the project and how to contribute, visit openmuscle.org.

Support

For support or questions about the muscle_sense_net model, please visit the project's GitHub repository or join the discussion on the openmuscle.org community forum.