Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: Ambulatory monitoring of human health is provided by a multi-component multi-sensor wireless wearable biosignal acquisition system comprising a torso device and a peripheral device communicating wirelessly, and a mobile phone for receiving collected data and uploading it over cellular network or WiFi to a remote computer for multivariate analysis. Biosignals include EKG and PPG, from which a determination of pulse transit time can be made.

Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: Ambulatory monitoring of human health is provided by a multi-component multi-sensor wireless wearable biosignal acquisition system comprising a torso device and a peripheral device communicating wirelessly, and a mobile phone for receiving collected data and uploading it over cellular network or WiFi to a remote computer for multivariate analysis. Biosignals include EKG and PPG, from which a determination of pulse transit time can be made.

Abstract: Efficient management of patient health of a population of patients, such as chronically ill patients living at home and monitored with remote continuous wearable or implantable physiology telemetry, is provided by means of a computer application for rendering a prioritized list of patients sortable according to a number of distinct criteria.

Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: Ambulatory monitoring of human health is provided by a multi-component multi-sensor wireless wearable biosignal acquisition system comprising a torso device and a peripheral device communicating wirelessly, and a mobile phone for receiving collected data and uploading it over cellular network or WiFi to a remote computer for multivariate analysis. Biosignals include EKG and PPG, from which a determination of pulse transit time can be made.

Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: An analytic apparatus and method is provided for diagnosis, prognosis and biomarker discovery using transcriptome data such as mRNA expression levels from microarrays, proteomic data, and metabolomic data. The invention provides for model-based analysis, especially using kernel-based models, and more particularly similarity-based models. Model-derived residuals advantageously provide a unique new tool for insights into disease mechanisms. Localization of models provides for improved model efficacy. The invention is capable of extracting useful information heretofore unavailable by other methods, relating to dynamics in cellular gene regulation, regulatory networks, biological pathways and metabolism.

Abstract: Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

Abstract: An analytic apparatus and method is provided for diagnosis, prognosis and biomarker discovery using transcriptome data such as mRNA expression levels from microarrays, proteomic data, and metabolomic data. The invention provides for model-based analysis, especially using kernel-based models, and more particularly similarity-based models. Model-derived residuals advantageously provide a unique new tool for insights into disease mechanisms. Localization of models provides for improved model efficacy. The invention is capable of extracting useful information heretofore unavailable by other methods, relating to dynamics in cellular gene regulation, regulatory networks, biological pathways and metabolism.

Abstract: A method for systematically configuring and deploying an empirical model used for fault detection and equipment health monitoring. The method is driven by a set of data preprocessing and model performance metrics subsystems that when applied to a raw data set, produce an optimal empirical model.

Abstract: A system and method for monitoring a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed using a sequential probability ratio test (“SPRT”). The invention employs empirically derived distributions in the SPRT to provide more accurate and sensitive alerts of impending faults, breakdowns and process deviations. The distributions can be generated from piecewise continuous approximation or spline functions based on the actual distribution of residual data to provide improved computational performance. The distributions can be provided before monitoring, or can be updated and determined during monitoring in an adaptive fashion.

Abstract: A system and method for monitoring a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed using a sequential probability ratio test (“SPRT”). The invention employs empirically derived distributions in the SPRT to provide more accurate and sensitive alerts of impending faults, breakdowns and process deviations. The distributions can be generated from piecewise continuous approximation or spline functions based on the actual distribution of residual data to provide improved computational performance. The distributions can be provided before monitoring, or can be updated and determined during monitoring in an adaptive fashion.

Abstract: A system for empirically diagnosing a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed for failure mode signature recognition. Residual values can also be tested for alert (non-zero) conditions, and patterns of alerts thus generated are analyzed for failure mode signature patterns. The system employs a similarity operator for signature recognition and also for parameter estimation. Failure modes are empirically determined, and precursor data is automatically analyzed to determine differentiable signatures for failure modes.