Abstract: A control system for administration of a drug comprises a drug administration actuator for administering the drug to a patient at a controllable dosage; a monitor for measuring an effect of the drug on the patient; and a controller configured to determine a control signal to the drug administration actuator; wherein the controller is configured to implement a closed loop model-predictive control scheme comprising, for each of a series of time steps, minimizing a cost function subject to one or more constraints to determine the control signal, the cost function based at least in part on a reference level and the monitor measurement; wherein the control signal is used as an input to an auxiliary model to estimate at least one concentration level of the drug in the patient; and wherein the constraints comprise at least one constraint on the estimate of the concentration level of the drug.

Abstract: A method includes obtaining operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller. The method also includes, during a training period, performing closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying clusters associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period, performing closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters.

Abstract: A control system for administration of a drug comprises a drug administration actuator for administering the drug to a patient at a controllable dosage; a monitor for measuring an effect of the drug on the patient; and a controller configured to determine a control signal to the drug administration actuator; wherein the controller is configured to implement a closed loop model-predictive control scheme comprising, for each of a series of time steps, minimizing a cost function subject to one or more constraints to determine the control signal, the cost function based at least in part on a reference level and the monitor measurement; wherein the control signal is used as an input to an auxiliary model to estimate at least one concentration level of the drug in the patient; and wherein the constraints comprise at least one constraint on the estimate of the concentration level of the drug.

Abstract: A control system for administration of a drug comprises a drug administration actuator for administering the drug to a patient at a controllable dosage; a monitor for measuring an effect of the drug on the patient; and a controller configured to determine a control signal to the drug administration actuator; wherein the controller is configured to implement a closed loop model-predictive control scheme comprising, for each of a series of time steps, minimizing a cost function subject to one or more constraints to determine the control signal, the cost function based at least in part on a reference level and the monitor measurement; wherein the control signal is used as an input to an auxiliary model to estimate at least one concentration level of the drug in the patient; and wherein the constraints comprise at least one constraint on the estimate of the concentration level of the drug.

Abstract: The invention relates to administration of clinical anesthesia. Particular embodiments provide systems and methods for controlled delivery of a combination of an analgesic agent and a hypnotic agent. More specifically, the invention relates to closed-loop control systems/methods for automatically controlling the administration of a combination of a hypnotic agent and an analgesic agent in a clinical anesthesia setting which incorporate feedback based on one or more indirect measures/indicia of analgesia. The invention further relates to such control systems/methods that account for limitations of such indirect measures/indicia of analgesia.

Abstract: The invention relates to administration of clinical anesthesia. Particular embodiments provide systems and methods for controlled delivery of a combination of an analgesic agent and a hypnotic agent. More specifically, the invention relates to closed-loop control systems/methods for automatically controlling the administration of a combination of a hypnotic agent and an analgesic agent in a clinical anesthesia setting which incorporate feedback based on one or more indirect measures/indicia of analgesia. The invention further relates to such control systems/methods that account for limitations of such indirect measures/indicia of analgesia.

Abstract: A method includes repeatedly identifying one or more values for one or more model parameters of at least one model associated with a process. The one or more values for the one or more model parameters are identified using data associated with the process. The method also includes clustering the values of the one or more model parameters into one or more clusters. The method further includes identifying one or more additional values for the one or more model parameters using additional data associated with the process. In addition, the method includes detecting a mismatch between the at least one model and the process in response to determining that at least some of the one or more additional values fall outside of the one or more clusters. The values could be clustered using a support vector machine.

Abstract: A method includes obtaining closed-loop data associated with operation of an industrial process controller, where the industrial process controller is configured to control at least part of an industrial process using at least one model. The method also includes generating at least one noise model associated with the industrial process controller using at least some of the closed-loop data. The method further includes filtering the closed-loop data based on the at least one noise model. In addition, the method includes generating one or more model parameters for the industrial process controller using the filtered closed-loop data.

Abstract: There is described are electroencephalography (EEG) device. The EEG device comprises one or more inputs for connecting via electrodes to a subject, and one or more DC/AC EEG amplifiers for amplifying electric potential signals from a subject. Each DC/AC EEG amplifier comprises a preamplifier connected to the one or more inputs and configured to amplify a signal received at the one or more inputs, the preamplifier having a differential gain set so as to have a common mode rejection ratio (CMRR) of at least 100 dB. Each DC/AC EEG amplifier further comprises an amplifier circuit connected to the preamplifier and configured to further amplify the signal, and, based thereon, output an output signal comprising a DC component having a frequency of less than 0.02 Hz.

Abstract: Sheetmaking cross-directional (CD) control requires a sophisticated model-based controller whose operation requires an accurate model of process behavior, but due to the complexity of the process, identifying these process models is challenging. Current techniques rely on open-loop process experimentation. Using non-causal scalar transfer functions for the steady-state CD process model and controller model avoid the problem of large dimensions associated with the CD process. These non-causal transfer functions can be represented by causal transfer functions that are equivalent to the non-causal ones in the sense of the output spectrum. A closed-loop optimal input design framework is proposed based on these causal equivalent models. CD actuators have responses in both sides along the cross direction which can be viewed as a non-causal behavior.

Abstract: The invention relates to administration of clinical anesthesia. Particular embodiments provide systems and methods for controlled delivery of a combination of an analgesic agent and a hypnotic agent. More specifically, the invention relates to closed-loop control systems/methods for automatically controlling the administration of a combination of a hypnotic agent and an analgesic agent in a clinical anesthesia setting which incorporate feedback based on one or more indirect measures/indicia of analgesia. The invention further relates to such control systems/methods that account for limitations of such indirect measures/indicia of analgesia.

Abstract: Methods, systems and related apparatus are provided to enable an electronic device to operate an external sensor comprising one or more emitters for emitting electromagnetic radiation of two different wavelengths and a detector for generating a response signal based on received electromagnetic radiation of the two different wavelengths connectable to an audio interface by applying a harmonic driving signal to a first contact and a second contact of the audio interface for driving the emitters of the external sensor, receiving the response signal at a third contact of the audio interface, demodulating and demultiplexing the response signal into a first wavelength response signal and a second wavelength response signal, analyzing the first and second wavelength response signals to determine one or more vital signs, and outputting the determined one or more vital signs.

Abstract: A control system for administration of a drug comprises a drug administration actuator for administering the drug to a patient at a controllable dosage; a monitor for measuring an effect of the drug on the patient; and a controller configured to determine a control signal to the drug administration actuator; wherein the controller is configured to implement a closed loop model-predictive control scheme comprising, for each of a series of time steps, minimizing a cost function subject to one or more constraints to determine the control signal, the cost function based at least in part on a reference level and the monitor measurement; wherein the control signal is used as an input to an auxiliary model to estimate at least one concentration level of the drug in the patient; and wherein the constraints comprise at least one constraint on the estimate of the concentration level of the drug.

Abstract: A method includes obtaining closed-loop data associated with operation of an industrial process controller, where the industrial process controller is configured to control at least part of an industrial process using at least one model. The method also includes generating at least one noise model associated with the industrial process controller using at least some of the closed-loop data. The method further includes filtering the closed-loop data based on the at least one noise model. In addition, the method includes generating one or more model parameters for the industrial process controller using the filtered closed-loop data.

Abstract: A method includes obtaining operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller. The method also includes, during a training period, performing closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying clusters associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period, performing closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters.

Abstract: A method includes repeatedly identifying one or more values for one or more model parameters of at least one model associated with a process. The one or more values for the one or more model parameters are identified using data associated with the process. The method also includes clustering the values of the one or more model parameters into one or more clusters. The method further includes identifying one or more additional values for the one or more model parameters using additional data associated with the process. In addition, the method includes detecting a mismatch between the at least one model and the process in response to determining that at least some of the one or more additional values fall outside of the one or more clusters. The values could be clustered using a support vector machine.

Abstract: Sheetmaking cross-directional (CD) control requires a sophisticated model-based controller whose operation requires an accurate model of process behavior, but due to the complexity of the process, identifying these process models is challenging. Current techniques rely on open-loop process experimentation. Using non-causal scalar transfer functions for the steady-state CD process model and controller model avoid the problem of large dimensions associated with the CD process. These non-causal transfer functions can be represented by causal transfer functions that are equivalent to the non-causal ones in the sense of the output spectrum. A closed-loop optimal input design framework is proposed based on these causal equivalent models. CD actuators have responses in both sides along the cross direction which can be viewed as a non-causal behavior.

Abstract: Systems and methods are provided for predicting a circadian state of an individual. The methods comprise: providing a model representative of the response of the circadian state to light stimulus, the model comprising at least one model variable representative of a probability distribution function (PDF) of a phase offset of the circadian state of the individual; and using the model to estimate an updated PDF of the phase offset, wherein using the model to estimate the updated PDF of the phase offset comprises performing a Bayesian estimation process commencing with an initial PDF of the phase offset and iterating toward the updated PDF of the phase offset.

Abstract: Methods, systems and related apparatus are provided to enable an electronic device to operate an external sensor comprising one or more emitters for emitting electromagnetic radiation of two different wavelengths and a detector for generating a response signal based on received electromagnetic radiation of the two different wavelengths connectable to an audio interface by applying a harmonic driving signal to a first contact and a second contact of the audio interface for driving the emitters of the external sensor, receiving the response signal at a third contact of the audio interface, demodulating and demultiplexing the response signal into a first wavelength response signal and a second wavelength response signal, analyzing the first and second wavelength response signals to determine one or more vital signs, and outputting the determined one or more vital signs.

Abstract: Methods, systems and related apparatus are provided to enable an electronic device to operate an external sensor comprising one or more emitters for emitting electromagnetic radiation of two different wavelengths and a detector for generating a response signal based on received electromagnetic radiation of the two different wavelengths connectable to an audio interface by applying a harmonic driving signal to a first contact and a second contact of the audio interface for driving the emitters of the external sensor, receiving the response signal at a third contact of the audio interface, demodulating and demultiplexing the response signal into a first wavelength response signal and a second wavelength response signal, analyzing the first and second wavelength response signals to determine one or more vital signs, and outputting the determined one or more vital signs.