J Clin Monit Comput - Dynamic behavior of BIS, M-entropy and neuroSENSE brain function monitors.

Tópicos

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Resumo

JECTIVES: The objective of this paper is to assess the suitability of brain function monitors for use in closed-loop anesthesia or sedation delivery. In such systems, monitors used as feedback sensors should preferably be Linear and Time Invariant (LTI) in order to limit sensor-induced uncertainty which can cause degraded performance. In this paper, we evaluate the suitability of the BIS A2000 (Aspect Medical Systems, MA), the M-Entropy Monitor (GE HealthCare), and the NeuroSENSE Monitor (NeuroWave Systems Inc, OH), by verifying whether their dynamic behavior conforms to the LTI hypothesis.METHODS: We subjected each monitor to two different composite EEG signals containing step-wise changes in cortical activity. The first signal was used to identify Linear Time-Invariant (LTI) models that mathematically capture the dynamic behavior of each monitor. The identification of the model parameters was carried out using standard Recursive Least Squares (RLS) estimation. The second signal was used to assess the performance of the model, by comparing the output of the monitor to the simulated output predicted by the model.RESULTS: While a LTI model was successfully derived for each monitor using the first signal, only the model derived for NeuroSENSE was capable to reliably predict the monitor output for the second input signals. This indicates that some algorithmic processes within the BIS A2000 and M-Entropy are non-linear and/or time variant.CONCLUSION: While both BIS and M-Entropy monitors have been successfully used in closed-loop systems, we were unable to obtain a unique LTI model that could capture their dynamic behavior during step-wise changes in cortical activity. The uncertainty in their output during rapid changes in cortical activity impose limitations in the ability of the controller to compensate for rapid changes in patients' cortical state, and pose additional difficulties in being able to provide mathematically proof for the stability of the overall closed-loop system. Conversely, the NeuroSENSE dynamic behavior can be fully captured by a linear and time invariant transfer function, which makes it better suited for closed-loop applications.

Resumo Limpo

jectiv object paper assess suitabl brain function monitor use closedloop anesthesia sedat deliveri system monitor use feedback sensor prefer linear time invari lti order limit sensorinduc uncertainti can caus degrad perform paper evalu suitabl bis aspect medic system ma mentropi monitor ge healthcar neurosens monitor neurowav system inc oh verifi whether dynam behavior conform lti hypothesismethod subject monitor two differ composit eeg signal contain stepwis chang cortic activ first signal use identifi linear timeinvari lti model mathemat captur dynam behavior monitor identif model paramet carri use standard recurs least squar rls estim second signal use assess perform model compar output monitor simul output predict modelresult lti model success deriv monitor use first signal model deriv neurosens capabl reliabl predict monitor output second input signal indic algorithm process within bis mentropi nonlinear andor time variantconclus bis mentropi monitor success use closedloop system unabl obtain uniqu lti model captur dynam behavior stepwis chang cortic activ uncertainti output rapid chang cortic activ impos limit abil control compens rapid chang patient cortic state pose addit difficulti abl provid mathemat proof stabil overal closedloop system convers neurosens dynam behavior can fulli captur linear time invari transfer function make better suit closedloop applic

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