One of the main problems encountered for determining depth of anaeshesia is to extract consistent and relevant measurementsas quick as possible. The AEP are able to provide parameters with anatomical significance while their characteristics reflect the way in which the brain reacts to a stimulus. By means of ARX modelling we have improved the SNR of AEP, which facilitates a faster deduction of the main parameters.
On-line analysis of averaged AEP, Autoregressive (ARX) modelled AEP and Spectral Edge Frequency of EEG for monitoring depth of Anaesthesia / L., Capitanio; E. W., Jensen; Filligoi, Giancarlo; B., Makovec; M., Gagliardi; S., Henneberg; P., Lidholm; S., Cerutti. - STAMPA. - 1:(1996), pp. 135-138. (Intervento presentato al convegno II IFMBE/IMIA International Workshop on Signal Interpretation tenutosi a Kanagawa nel 23-28 Sett 1996).
On-line analysis of averaged AEP, Autoregressive (ARX) modelled AEP and Spectral Edge Frequency of EEG for monitoring depth of Anaesthesia
FILLIGOI, Giancarlo;
1996
Abstract
One of the main problems encountered for determining depth of anaeshesia is to extract consistent and relevant measurementsas quick as possible. The AEP are able to provide parameters with anatomical significance while their characteristics reflect the way in which the brain reacts to a stimulus. By means of ARX modelling we have improved the SNR of AEP, which facilitates a faster deduction of the main parameters.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
