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Adaptive algorithm for automatic analysis of electronystagmographic signals

The vestibular system is important for the maintenance of static and dynamic equilibrium of the human body. Dysfunctions within this system may lead to abnormal reflex eye movements known as nystagmus. It is possible to diagnose several pathologies of the human vestibular system through the analysis of this signal. In a previous work a computational algorithm that automatically evaluates the nystagmus' slow component velocity was developed. This algorithm gave good results when compared to the clinical analysis, but it did not foresee the possibility of expressive changes in the signal to noise ratio. Here, the author presents a new algorithm that monitors the level of noise associated to the signal and modifies its parameters in such a way as to improve the results. Comparisons between these two algorithms were done and the results indicate a clear superiority of this new technique over the previous one.