Thesis Project Form

In high-density electromyography (hd-EMG), electrical muscle activity is recorded using matrix electrodes comprising many detection points. This provides a high resolution spatially distributed snapshot of activity across many muscles. This information can then be used to e.g. recognize wrist and hand gestures that the
subject performs, thereby enabling gesture recognition for the control of external systems.

The general objective is to develop novel approaches to recording and processing high-density electromyography.
Main activities include:
Definition of an experimental protocol for data collection using a technology developed at AAU (Neuraloop).
Using machine learning to process the collected data and assess the developed pattern classification and regression using both offline analysis and online control.

The trainee will start by reviewing the literature about the use of HD EMG for gesture recognition, and then he will be trained to set up and conduct the recording. Together with the supervisor, the trainee will define an experimental protocol for data collection and processing.
As a final step, the trainee will prepare a project report presenting the methods and results.