Abstract: Some embodiments of the invention provide a system to monitor a patient. In some aspects, a signal representing a value of a physiological parameter is received from a monitoring device. The received value is a value that caused the monitoring device to trigger an alarm associated with the psychological parameter. A notification is determined based on the received signal and on a second signal that represents a value of a second physiological parameter. The notification is then presented to an operator.

Abstract: Some embodiments of the invention provide a system to monitor a patient. In some aspects, a signal representing a value of a physiological parameter is received from a monitoring device. The received value is a value that caused the monitoring device to trigger an alarm associated with the psychological parameter. A notification is determined based on the received signal and on a second signal that represents a value of a second physiological parameter. The notification is then presented to an operator.

Abstract: A system and method for intelligent assignment, scheduling and notification for better patient management is provided. The method includes registering at least one clinician along with a schedule of predetermined tasks and availability for the at least one clinician; registering at least one patient; assigning registered patients to the at least one registered clinician; generating an event task for the at least one registered clinician; determining if the at least one clinician is available; and if the at least one clinician is unavailable, assigning the event task to a next available registered clinician. The system will automatically route the event task, e.g., an alarm, with necessary information to a wireless device worn by the responsible clinician. Alarms could be generated by medical equipment, a medication and task scheduler, a central monitoring system, or triggered by abnormal test results.

Abstract: Some embodiments of the invention provide a system to monitor a patient. In some aspects, a signal representing a value of a physiological parameter is received from a monitoring device. The received value is a value that caused the monitoring device to trigger an alarm associated with the psychological parameter. A notification is determined based on the received signal and on a second signal that represents a value of a second physiological parameter. The notification is then presented to an operator.

Abstract: A system and method for providing treatment and outcome measurement analysis. In one aspect, real-time treatment options having statistical outcome data are generated and provided to users. Data from remote data sources is compiled onto a server and used to generate a decision support model. The user can then present patient features to the decision support model, and will be provided with a set of possible treatment options with statistical information in return. When a user selects a treatment option, an outcome analysis is performed to assess the patient's progress. The results of the outcome analysis are input into the server to update the decision support model.

Abstract: A graphical user interface provides a real-time information display for a supervising engineer in charge of turbine operation so that critical parameter values and undesirable combinations of operating conditions are readily observed and deviations are made apparent so that corrective action can be initiated rapidly. An overview of the operating situation is made more readily apparent by representing the operating expansion and compression processes by lines on a Mollier enthalpy/entropy chart. In combination, real-time parameter values and parameter trends are also presented. Using the Mollier chart information in conjunction with trend and real-time information, the supervising engineer can more quickly identify and correct undesirable and potentially troublesome operation conditions.

Abstract: A method for blade temp estimation in a steam turbine utilizes measurement values including pressure and temperature at locations other than directly at the blades, principally at the input and output stages. Initially, blade temperature is simulated by using a water/steam cycle analysis program as well as by directed experiments. An artificial neural network (ANN) is trained by presenting the measurement values and the blade temp values. In a hybrid approach, 5 measured values are utilized. A subset of 4 parameter values is used for training the ANN and another subset of 3 values is used for performing a calculation for another intermediate parameter. Using the intermediate parameter and one of the 5 measured values, a blade temperature is calculated.