Abstract: A waveform anomaly detection system is provided that automatically detects and tags waveform data patterns in physiological patient (time-series) data that match predefined, clinically validated patterns, to enable clinicians to match and corroborate their own observations with tool-triggered findings. As a result, clinicians may make more informed clinical decisions without having to manually review enormous amounts of time-series data. Additionally, when anomalous waveform patterns are detected, relevant patient data from an electronic medical record (EMR) or similar databases and/or platforms may be automatically retrieved and integrated into the waveform data, such that the integrated data may be viewed together on a display device. The data may be stored with the anomalous waveform patterns in a database of the waveform anomaly detection system, where analysis results can be accessed conveniently by a caregiver of the patient, for example, using a personal computing device such as a smart phone.

Abstract: Systems and methods are disclosed for tagging anatomical locations of monitoring devices on a patient in a reference image on an application. The application excludes data from the monitoring devices from analysis by a clinical decision support system when the monitoring devices are misplaced, for example in locations other than the tagged anatomical locations.

Abstract: The monitoring system for presenting a health state of a subject is disclosed. The monitoring system includes a processor for analyzing multiple health parameters associated with the subject. Based on this analysis, a health state indicator includes multiple gauges for visually presenting the health state of the subject. A gauge orients with respect to a gauge reference line based on the analyzed health parameters. In an embodiment, an interface element for visually presenting the health state of the subject in a monitoring system is disclosed. The interface element includes a health state indicator. The health state indicator includes multiple gauges, wherein one or more gauges orient with respect to one or more gauge reference lines based on analysis of the multiple health parameters to visually represent the health state of the subject. The health parameters are analyzed by the monitoring system.

Abstract: The monitoring system for presenting a health state of a subject is disclosed. The monitoring system includes a processor for analyzing multiple health parameters associated with the subject. Based on this analysis, a health state indicator includes multiple gauges for visually presenting the health state of the subject. A gauge orients with respect to a gauge reference line based on the analyzed health parameters. In an embodiment, an interface element for visually presenting the health state of the subject in a monitoring system is disclosed. The interface element includes a health state indicator. The health state indicator includes multiple gauges, wherein one or more gauges orient with respect to one or more gauge reference lines based on analysis of the multiple health parameters to visually represent the health state of the subject. The health parameters are analyzed by the monitoring system.

Abstract: In one embodiment, a method of using a patient monitoring network is provided. The method comprises steps of storing an association data at a primary server unit, the association data mapping a caregiver with at least one patient associated with the caregiver, storing an object data of at least one patient at a patient monitor coupled to the primary server unit, the object data comprising an identification data and a patient data of the patient, receiving a query at the patient monitor by the caregiver, fetching the association data of the caregiver from the primary server unit, displaying the identification data of at least one patient associated with the caregiver at the patient monitor, obtaining a selection for the patient at the patient monitor and displaying the patient data of the patient at the patient monitor.