Optimization of the Vagus Nerve Stimulation Parameters with CI-Methods

In order to improve the Vagus Nerve Stimulation (VNS) statistical efficacy increase for certain parameter vectors was investigated. Such vectors are used in real cases. Although immediate tests on humans are not possible it was possible to find rats as adequate substitute models. The rats were stimulated with a protocol of 81 parameter vectors. Their physical response was recorded. Each rat is different but it is assumed that for some vectors similar response will occur. If only enough rats were recorded then a statistically safe prediction could be made about what parameter vectors will result in effects mostly desired by the therapist. It is the primary goal of the project to find similarities in different response cases for some of the typical vectors and eventually provide deeper insights on the treatment. The project faces extremely large data amounts from data acquisition. Methods of Computational Intelligence (CI) are used for the conversion of data to knowledge. After conventional data pre-processing evolutionarily designed artificial neural networks are used in order to evaluate available data and to help medical staff verify their medical thesis.