An Improved Method of Nystagmus Segmentation Using Adaptive Modification of Time-Frequency Signal Representation
نویسنده
چکیده
The present work describes an application of adaptative signal filtration in the time-scale domain using a pair of reversible wavelet transformations to the precise delimitation of the nystagmus quick and slow phases in an electronystagmogram. In common used methods the main source of inaccuracies in diagnostics parameters is the imprecision in phases delimitation (nystagmus segmentation) caused by an aggresive low-pass signal filtering. Since the signal is very fragile (typically 5mV/deg) and the acquisition environnement is not stable in time, the need of adaptive filtration appears. The use of reversible wavelet transform of ENG signal, being limited only by uncertainty relation, guarantees the highest possible precision. An improvement in quality of the calculated diagnostic parameters is expressed by a simultaneous occurrence of minimum inaccuracies and a minimum number of interpretation errors.
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