Abstract: A system, method and apparatus is disclosed, comprising a biomathetical model for optimizing cognitive performance in the face of sleep deprivation that integrates novel and nonobvious biomathematical models for quantifying performance impairment for both chronic sleep restriction and total sleep deprivation; the dose-dependent effects of caffeine on human vigilance; and the pheonotypical response of a particular user to caffeine dosing, chronic sleep restriction and total sleep deprivation in user-friendly software application which itself may be part of a networked system.

Abstract: A method of estimating a body temperature of an individual based on physiological data including a heart rate received from at least one sensor 510 and received environmental data. The physiological data and the environmental data are inputted into a model present on a processor 520. The model generates an estimated body temperature and an estimated physiological condition based on the inputs. The processor 520 compares the estimated physiological condition to a measured physiological condition in the physiological data. A controller 530 modifies at least one parameter in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold.

Abstract: An embodiment of the invention provides a method of estimating a body temperature of an individual where physiological data is received from at least one sensor 510. Environmental data is received and the physiological data and the environmental data are input into a model. The model generates an estimated body temperature and an estimated physiological condition based on the physiological data and the environmental data. A processor 520 compares the estimated physiological condition to a measured physiological condition in the physiological data. A controller 530 modifies at least one parameter in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold.

Abstract: A system and method using a biomathetical model in conjunction with an optimization method for an individuals alertness impairment at a future time based on a known sleep schedule by adjusting the intake of caffeine over that schedule. In a further embodiment, placing constraints on the frequency, the dose amount, and/or total amount consumed over the course of the future schedule. In a further embodiment, optimizing the sleep schedule (prior to or independent of caffeine optimization) to decrease the individuals alertness impairment at the future time(s). In a further embodiment, adjust both the sleep schedule and caffeine intake to decrease the individuals alertness impairment at the future time(s). In at least one embodiment, the system including a mobile based system and/or a networked computer-based system.

Abstract: A method and a system analyze an individual's physiological data to identify aberrant vital-signs patterns and estimate an infection probability. The identification includes determining a score based on the current vital-sign measurements, and the mean and standard deviation of baseline vital-signs values. In one embodiment, the mean and the standard deviation are selected based on the corresponding baseline time window and activity bin of the current vital-sign measurement. The score is identified as normal when between two thresholds and aberrant outside of those two thresholds.

Abstract: A system, method and apparatus is disclosed, comprising a biomathetical model for optimizing cognitive performance in the face of sleep deprivation that integrates novel and nonobvious biomathematical models for quantifying performance impairment for both chronic sleep restriction and total sleep deprivation; the dose-dependent effects of caffeine on human vigilance; and the pheonotypical response of a particular user to caffeine dosing, chronic sleep restriction and total sleep deprivation in user-friendly software application which itself may be part of a networked system.

Abstract: A system, method and apparatus is disclosed, comprising a biomathetical model for optimizing cognitive performance in the face of sleep deprivation that integrates novel and nonobvious biomathematical models for quantifying performance impairment for both chronic sleep restriction and total sleep deprivation; the dose-dependent effects of caffeine on human vigilance; and the pheonotypical response of a particular user to caffeine dosing, chronic sleep restriction and total sleep deprivation in user-friendly software application which itself may be part of a networked system.

Abstract: A method of estimating a body temperature of an individual based on physiological data including a heart rate received from at least one sensor 510 and received environmental data. The physiological data and the environmental data are inputted into a model present on a processor 520. The model generates an estimated body temperature and an estimated physiological condition based on the inputs. The processor 520 compares the estimated physiological condition to a measured physiological condition in the physiological data. A controller 530 modifies at least one parameter in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold.

Abstract: An embodiment of the invention provides a method of estimating a body temperature of an individual where physiological data is received from at least one sensor 510. Environmental data is received and the physiological data and the environmental data are input into a model. The model generates an estimated body temperature and an estimated physiological condition based on the physiological data and the environmental data. A processor 520 compares the estimated physiological condition to a measured physiological condition in the physiological data. A controller 530 modifies at least one parameter in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold.

Abstract: A system, method and apparatus is disclosed, comprising a biomathetical model for optimizing cognitive performance in the face of sleep deprivation that integrates novel and nonobvious biomathematical models for quantifying performance impairment for both chronic sleep restriction and total sleep deprivation; the dose-dependent effects of caffeine on human vigilance; and the pheonotypical response of a particular user to caffeine dosing, chronic sleep restriction and total sleep deprivation in user-friendly software application which itself may be part of a networked system.

Abstract: A system is disclosed having a storage, a communications module for interacting with a medical measurement device, an analysis controller, and a test module that allows for the testing and evaluating of decision-support algorithms. A method for testing decision-support algorithms is disclosed having the steps of receiving into storage of a ruggedized, compact computer at least one decision-support algorithm; detecting with a communications module the initiation of a vital-sign monitoring session; receiving and storing vital-sign information into storage by the communications module; pushing the stored vital-sign information by an analysis controller to a test module running the stored at least one decision-support algorithm; and providing at least one output from the decision-support algorithm to at least one of a database and a display.

Abstract: A system is disclosed having a storage, a communications module for interacting with a medical measurement device, an analysis controller, and a test module that allows for the testing and evaluating of decision-support algorithms. A method for testing decision-support algorithms is disclosed having the steps of receiving into storage of a ruggedized, compact computer at least one decision-support algorithm; detecting with a communications module the initiation of a vital-sign monitoring session; receiving and storing vital-sign information into storage by the communications module; pushing the stored vital-sign information by an analysis controller to a test module running the stored at least one decision-support algorithm; and providing at least one output from the decision-support algorithm to at least one of a database and a display.

Abstract: A system is disclosed having a storage, a communications module for interacting with a medical measurement device, an analysis controller, and a test module that allows for the testing and evaluating of decision-support algorithms. A method for testing decision-support algorithms is disclosed having the steps of receiving into storage of a ruggedized, compact computer at least one decision-support algorithm; detecting with a communications module the initiation of a vital-sign monitoring session; receiving and storing vital-sign information into storage by the communications module; pushing the stored vital-sign information by an analysis controller to a test module running the stored at least one decision-support algorithm; and providing at least one output from the decision-support algorithm to at least one of a database and a display.

Abstract: A system is disclosed having a storage, a communications module for interacting with a medical measurement device, an analysis controller, and a test module that allows for the testing and evaluating of decision-support algorithms. A method for testing decision-support algorithms is disclosed having the steps of receiving into storage of a ruggedized, compact computer at least one decision-support algorithm; detecting with a communications module the initiation of a vital-sign monitoring session; receiving and storing vital-sign information into storage by the communications module; pushing the stored vital-sign information by an analysis controller to a test module running the stored at least one decision-support algorithm; and providing at least one output from the decision-support algorithm to at least one of a database and a display.

Abstract: A system is disclosed having a storage, a communications module for interacting with a medical measurement device, an analysis controller, and a test module that allows for the testing and evaluating of decision-support algorithms. A method for testing decision-support algorithms is disclosed having the steps of receiving into storage of a ruggedized, compact computer at least one decision-support algorithm; detecting with a communications module the initiation of a vital-sign monitoring session; receiving and storing vital-sign information into storage by the communications module; pushing the stored vital-sign information by an analysis controller to a test module running the stored at least one decision-support algorithm; and providing at least one output from the decision-support algorithm to at least one of a database and a display.

Abstract: A system is disclosed having a storage, a communications module for interacting with a medical measurement device, an analysis controller, and a test module that allows for the testing and evaluating of decision-support algorithms. A method for testing decision-support algorithms is disclosed having the steps of receiving into storage of a ruggedized, compact computer at least one decision-support algorithm; detecting with a communications module the initiation of a vital-sign monitoring session; receiving and storing vital-sign information into storage by the communications module; pushing the stored vital-sign information by an analysis controller to a test module running the stored at least one decision-support algorithm; and providing at least one output from the decision-support algorithm to at least one of a database and a display.

Abstract: A signal processing technique which correlates eddy current inspection data from a tube having a critical tubing defect with a range of predicted burst pressures for the tube is provided. The method can directly correlate the raw eddy current inspection data representing the critical tubing defect with the range of burst pressures using a regression technique, preferably an artificial neural network. Alternatively, the technique deconvolves the raw eddy current inspection data into a set of undistorted signals, each of which represents a separate defect of the tube. The undistorted defect signal which represents the critical tubing defect is related to a range of burst pressures utilizing a regression technique.

Abstract: The control of emissions from fossil-fired boilers wherein an injection of substances above the primary combustion zone employs multi-layer feedforward artificial neural networks for modeling static nonlinear relationships between the distribution of injected substances into the upper region of the furnace and the emissions exiting the furnace. Multivariable nonlinear constrained optimization algorithms use the mathematical expressions from the artificial neural networks to provide the optimal substance distribution that minimizes emission levels for a given total substance injection rate.

Abstract: A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles.

Abstract: A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics.