NeuroVista Corporation Patent applications |
Patent application number | Title | Published |
20130151166 | Reduction Of Classification Error Rates And Monitoring System Using An Artificial Class - Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class. | 06-13-2013 |
20130046358 | Systems and Methods of Reducing Artifact in Neurological Stimulation Systems - Systems and methods for neuromonitoring a subject are described. The system may include a stimulation assembly including a pulse generator that generates one or more stimulus waveforms; an electrode array coupled to the stimulation assembly and configured to deliver a stimulation signal to nervous system of the subject; a sensing assembly adapted to acquire a signal from a subject indicative of the subject's brain activity; a power supply configured to supply power to the stimulation assembly and the sensing assembly; and a timing controller programmed to control the use of the power supply by the stimulation assembly and the sensing assembly, said timing controller being programmed to control the time the sensing assembly is powered to acquire the signal to be substantially different than the time the stimulation assembly is powered to stimulate the subject. | 02-21-2013 |
20120143017 | Classification of patient condition using known and artifical classes - Methods of classifying a subject's condition are described. The method includes: receiving measured signals from the subject; processing the measured signals using a computing device to identify a class associated with an identified condition of the subject; introducing an artificial class, the artificial class being associated with an unknown condition of the subject; classifying a feature vector from the subject into the identified class or the artificial class; and generating a signal in response to classifying the feature vector. The measured signals from the subject may include at least one signal extracted from brain activity of the subject. | 06-07-2012 |
20110035689 | Reduction Of Classification Error Rates And Monitoring System Using An Artificial Class - Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class. | 02-10-2011 |
20100217348 | Systems for Monitoring a Patient's Neurological Disease State - The present invention provides methods and systems for modulating a patient's neurological disease state. In one embodiment, the system comprises one or more sensors that sense at least one signal that comprise a characteristic that is indicative of a neurological disease state. A signal processing assembly is in communication with the one or more sensors and processes the at least one signal to estimate the neurological disease state and to generate a therapy to the patient that is based at least in part on the estimated neurological disease state. A treatment assembly is in communication with the signal processing assembly and delivers the therapy to a nervous system component of the patient. | 08-26-2010 |
20100198763 | Reduction Of Classification Error Rates And Monitoring System Using An Artificial Class - Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class. | 08-05-2010 |