Detection of cluster in Self-Organizing Maps for controlling a prostheses using nerve signals.
Martin Bogdan, Wolfgang Rosenstiel · Publikation Server (Leipzig University) · 2001
In order to control a prostheses by means of biological nerve signals, a self-organizing map (SOM) has been used to classify nerve signals recorded by a regeneration type neurosensor. The trained SOM contains the information about the relation between the recorded nerve signal and the winning neuron of the SOM. Classes of nerve signals red by de ned axons can be found in cluster on the SOM. For controlling a prostheses, the clusters on the SOM must be assigned to an action of the prostheses. Since the medical stu is usually not experienced to identify the clusters within the SOM we have developed Clusot, an algorithm that de nes automatically clusters within SOMs. After a short introduction to the project of controlling a prostheses by nerve signals, we present the signal processing of the project. In this paper, we focus on the automatic detection of clusters within a trained SOM using Clusot. Clusot will be explained within the context of the project in question.