Abstract: The present invention relates to a physiological monitor and system, particularly to an electroencephalogram (EEG) monitor and system, and a method of detecting the presence and absence of artifacts and possibly removing artifacts from an EEG, other physiological signal or sensor signal without corrupting or compromising the signal. The accurate, real-time detection of the presence or absence of artifacts and removal of artifacts in EEG or other signals allows for increased reliability in the efficacy of those signals. The strategy of rejecting artifact-corrupted EEG can result in unacceptable data loss, and asking subjects to minimize movements in order to minimize artifacts is not always feasible. The present invention allows for increased accuracy in detection and removal of artifacts from physiological signals, substantially in real time, and without loss or corruption of signal or data in order to increase the accuracy of such signals for diagnosis and treatment purposes.

Abstract: Electrodes for use in electroencephalographic recording, including consciousness and seizure monitoring applications, have novel features that speed, facilitate or enforce proper placement of the electrodes, including aligning tabs and arrowed aligning juts, color coding, and an insulating bridge between reference and ground electrodes which ensures a safe application distance between the conductive regions of the two electrodes in the event of cardiac defibrillation. A method of using a set of four such electrodes is also disclosed.

Abstract: The present invention relates to a quantitative electroencephalogram (QEEG) monitor and system capable of monitoring and displaying simultaneously neuropathological characteristic and activity of both sides of a subject's brain. The methods include various indices and examination of differences in these indices by which neurophysiological conditions or problems can be identified and treated. These methods, and the systems and devices using these methods preferably can be used for identifying these neurophysiological conditions or brain dysfunction with monitors and methods for seizure detection, for sedation monitoring, for anesthesia monitoring, and the like. These bilateral brain monitoring methods and systems, and the devices using these methods can be used by individuals or clinicians with little or no training in signal analysis or processing. These bilateral monitoring methods can also be used in a range of applications.

Abstract: The present invention relates to a method of signal processing of electrograms for use in medical devices, preferably by time-frequency transforms. The present invention additionally relates to a system for receiving and analyzing such signals. The present invention preferably is a method utilizing the time-frequency transforms, such as wavelet transforms, for the purpose of artifact removal from EGs. These transforms decompose a signal in both time and frequency domains, and therefore, are well suited for non-stationary signal analysis. As a result, dissimilar signal features are well localized both in time and frequency, which potentially provides a good separation between the signal of interest and artifacts. This particularly applies to large-amplitude artifacts corrupting EGs.

Abstract: A method and apparatus to monitor and control the anesthesia state of a patient undergoing general anesthesia is provided. Previous automated systems to monitor the anesthesia state of a patient undergoing general anesthesia involve a significant time delay between the patient's true anesthesia state and the computed indices. The present invention reduces this time delay by using a novel analysis technique applied to spontaneous electrophysiological activity. A transformation and statistical analysis of the observed electrophysiological activity is conducted and compared to reference data to provide numerical indicators. In addition, these indicators are consistent with the levels of depression of patients CNS and ANS states. This method is illustrated in detail by CNS monitoring of electroencephalogram signals.

Abstract: The present invention, herein is a method and apparatus that significantly limits the effect of high frequency (“HF”) interferences on acquired electro-physiological signals, such as the EEG and EMG. Preferably, this method comprises of two separate electronic circuitries and steps or electronics for processing the signals. One circuit is used to block the transmission of HF interferences to the instrumentation amplifiers. It is comprised of a front-end active filter, a low frequency electromagnetic interference (“EMI”) shield, and an isolation barrier interface which isolates the patient from earth ground. The second circuit is used to measure the difference in potential between the two isolated sides of the isolation barrier. This so-called “cross-barrier” voltage is directly representative of the interference level that the instrumentation amplifier is subjected to. This circuit is used to confirm that the acquired signals are not corrupted by the interference.

Abstract: A method and apparatus to monitor the neurologic state of a patient undergoing general anesthesia is provided. Previous automated systems to monitor the neurologic state of a patient undergoing general anesthesia involve a significant time delay between the patients true hypnotic state and the computed indices. The present invention reduces this time delay by using a different analysis technique applied to spontaneous EEG. A wavelet decomposition and statistical analysis of the observed EEG is conducted and compared to reference data to provide a numerical indicator. In addition, this indicator is more consistent with the patient's loss of consciousness indicated by the loss of count event than previous systems.

Abstract: A method and apparatus to monitor the neurologic state of a patient undergoing general anesthesia is provided. Previous automated systems to monitor the neurologic state of a patient undergoing general anesthesia involve a significant time delay between the patient's true hypnotic state and the computed indices. The present invention reduces this time delay by using a different analysis technique applied to spontaneous EEG. A wavelet decomposition and statistical analysis of the observed EEG is conducted and compared to reference data to provide a numerical indicator. In addition, this indicator is more consistent with the patient's loss of consciousness indicated by the loss of count event than previous systems.

Abstract: A method and apparatus to monitor the neurologic state of a patient undergoing general anesthesia is provided. Previous automated systems to monitor the neurologic state of a patient undergoing general anesthesia involve a significant time delay between the patient's true hypnotic state and the computed indices. The present invention reduces this time delay by using a different analysis technique applied to spontaneous EEG. A wavelet decomposition and statistical analysis of the observed EEG is conducted and compared to reference data to provide a numerical indicator. In addition, this indicator is more consistent with the patient's loss of consciousness indicated by the loss of count event than previous systems.