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Functional near-infrared spectroscopy (fNIRS) is a powerful tool for monitoring brain functional activities. Due to its non-invasive and non-restraining nature, fNIRS has found broad applications in brain functional studies. However, for fNIRS to work well, it is important to reduce its sensitivity to motion artifacts. We propose a new wavelet-based method(More)
OBJECTIVES 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(More)
Blood pressure measurement is performed either invasively by an intra arterial catheter or noninvasively by cuff sphygmomanometry. The invasive method is continuous and accurate but has increased risk; the cuff is safe but less reliable and infrequent. A reliable continuous noninvasive blood pressure measurement is highly desirable. While the possibility of(More)
—The anesthesia community has recently witnessed numerous advances in the monitoring of the anesthetic state. This development has spurred a renewed interest in the automation of clinical anesthesia. While this subject was the apanage of researchers with strong clinical background, recently the control community became also involved. The collaborative(More)
This tutorial paper looks back at almost 50 years of adaptive control trying to establish how much more we need to secure for the industrial community an adaptive controller which will be used and referred to with the same ease as PID controllers are now. Since the first commercial adaptive controller, significant progress in the design and analysis of(More)
Visual displays and auditory alarms are used to convey information on physiological variables in an operating room. However, the exponential growth in the number of physiological variables and the high probability of false alarms has amplified demands on the clinician's attention. We have extended existing tactile technology to improve situational awareness(More)
We describe a novel algorithm for the prediction of epileptic seizures using scalp EEG. The method is based on the analysis of the positive zero-crossing interval series of the EEG signal and its first and second derivatives as a measure of brain dynamics. In a moving-window analysis, we estimated the probability density of these intervals and computed the(More)
Electroconvulsive therapy (ECT) is an effective treatment for severe depression. In this paper, we have used an algorithm based on wavelet packet (WP) analysis of EEG signals to detect seizures induced by ECT. After determining dominant frequency bands in the ictal period during ECT, the energy ratio of these bands was computed using the corresponding WP(More)
The first study with a PID controller based automatic drug delivery system for propofol anesthesia in children is presented. It is shown that a robustly tuned PID controller is capable of delivering safe and adequate anesthesia. The design process of the control system is reviewed. Results are discussed and compared to those of two previous studies in(More)
In this paper, we propose a novel wavelet-based algorithm for the detection of epileptic seizures. The algorithm is based on the recognition of rhythmic activities associated with ictal states in surface EEG recordings. Using a moving-window analysis, we first decomposed each EEG segment into a wavelet packet tree. Then, we extracted the coefficients(More)