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Algorithms for analysis of neural modulations in a vestibular prosthesis

Author(s):

C. Fischer
Conference/Journal:

Master Thesis,FS 09
Abstract:

In the human body, all sensory information is typically transmitted via neurons. However, if an organ (e.g. cochlea, vestibular organs) fails, the patient lacks all respective information even if the neurons are still functional. The idea of a neural prosthesis is to replace inputs from an organ by electrical stimulation. This requires good knowledge on how electrical stimulation interacts with the still intact neurons, specifically how it evokes neural responses and how these responses can be recorded and processed. In this thesis, algorithms for the analysis of such electrically evoked neural responses are investigated. Electrical stimulation introduces distortions, so-called artifacts, in the recording. These artifacts can cause saturation of the recording amplifiers and obscure the neural response. Therefore, a first challenge in the analysis of electrically evoked neural responses is to find methods to deal with these artifacts. To that end, different hardware and software approaches are investigated and compared. After preprocessing the data by removing the artifacts, the neural response is extracted. As the signal to noise ratio in neural recordings is usually low, special methods to detect and quantify neural activity are required. To that end, common analysis methods for local and distributed neural information are implemented and tested on an artificial data set. The results are then confirmed with physiological data. In a last step, three methods for the detection of changes in neural activity are tested on the extracted neural response. They facilitate activity onset detection without human interference. This is important for future online applications, such as a neural prosthesis, where changes in neural activity can serve as feedback in a closed loop control system.

Year:

2009
Type of Publication:

(12)Diploma/Master Thesis
Supervisor:

M. Morari

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2009:IFA_3444
}
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