Identification of a neuroelectric system involving a single input and a single output

A. G. Rigas, P. Liatsis

Research output: Contribution to journalArticlepeer-review

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In this work, we identify a neuroelectric system by using a stochastic model of Volterra type. The neuroelectric system is called muscle spindle and plays a critical role in the initiation of movement and in the maintenance of posture. In order to identify the stochastic model we use spectral analysis techniques of stationary point processes, which are based on Welch's method. New asymptotic results for the gain, phase and impulse function of the system based on the Welch's method are obtained. These results are used in examining the behaviour of the muscle spindle under two different experimental conditions: (a) when there is no input present and (b) when an input is present. The presence of the input drastically modifies the behaviour of the muscle spindle. It is shown from the estimates of the gain and phase that the system behaves as a high-pass filter with the input leading the output by about 30 ms. This result is also verified from the estimate of the impulse function which indicates that the system does not respond for about 30 ms.

Original languageBritish English
Pages (from-to)1883-1894
Number of pages12
JournalSignal Processing
Issue number9
StatePublished - Sep 2000


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