Abstract: A security gateway for touch-free infectious disease screening includes a contactless sensor, a memory and a processor. The contactless sensor is configured to obtain health readings of a subject. The memory stores instructions. The processor executes the instructions. When executed by the processor, the instructions cause the security gateway to measure vital signs based on the health readings of the subject, and determine whether to allow access to a premise based on the vital signs.

Abstract: The present disclosure pertains to a system for providing client-side physiological condition estimations during a live video session. In some embodiments, the system includes a first client computer system that is caused to: (i) store a neural network on one or more computer-readable storage media of the first client computer system, (ii) obtain a live video stream of an individual via a camera of the first client computer system during a video streaming session between the first client computer system and a second client computer system, (iii) provide, during the video streaming session, video data of the live video stream as input to the neural network to obtain physiological condition information from the neural network, and (iv) provide, during the video streaming session, the physiological condition information for presentation at the second client computer system.

Abstract: The present disclosure pertains to a system for providing client-side physiological condition estimations during a live video session. In some embodiments, the system includes a first client computer system that is caused to: (i) store a neural network on one or more computer-readable storage media of the first client computer system, (ii) obtain a live video stream of an individual via a camera of the first client computer system during a video streaming session between the first client computer system and a second client computer system, (iii) provide, during the video streaming session, video data of the live video stream as input to the neural network to obtain physiological condition information from the neural network, and (iv) provide, during the video streaming session, the physiological condition information for presentation at the second client computer system.

Abstract: Methods and systems for monitoring patient physiological status. The system may include a source of vital sign measurements for a patient, a trained machine learning model that receives the vital sign measurements and provides an output related to the physiological status of the patient, and an interface configured to present the output to an operator. The method may include receiving, at a trained machine learning model, at least one physiological measurement, demographic information point, or treatment plan for a patient, providing, using the trained machine learning model, an output relating to the physiological status of the patient, and presenting, using an interface, the output to an operator.

Abstract: A method of monitoring a patient includes receiving patient data from one or more sensors a patient monitoring system, comparing the received patient data with preselected thresholds indicative of patient status, determining a patient status from comparing the received patient data with the preselected thresholds, and adjusting a sampling frequency of the one or more sensors based on the determined patient status.

Abstract: A method includes obtaining an electrical signal that includes a set of at least two sensed physiologic measurements of a patient, comparing the at least two physiologic measurements with a predetermined physiologic measurement range, identifying data required to determine a probability and a severity of a condition of interest of the patient, in response to determining the at least two physiologic measurements do not satisfy the physiologic measurement range, receiving the identified data in electronic format, determining a first probability and a first severity of the condition of interest based on the received identified data, determining a recommended course of action for the patient based on the first probability and the first severity, resources of a healthcare facility, and an event guideline; and causing a display to visually present the first probability and first severity and the recommended course of action.

Abstract: A patient monitor system (10) includes a signal processor (30) which analyzes signals from physiological parameter sensors (20) to derive physiological data values, plots, and alarms. A display (12) displays physiological values and plots (42). An advisor engine, routine, or processor (34) is connected with the signal processor to analyze at least alarm occurrences, also in combination with user interactions, and provide directly actionable advice for reducing alarm frequency which is displayed unobtrusively on the display. The directly actionable advice includes specific actions or adjustments which are specific to a current patient, a present situation, or a present mode or setting of the patient monitor system. The unobtrusively displayed directly actionable advice is displayed without the use requesting it.

Abstract: A method for assisting a user in selecting audible alarm settings of a patient monitoring system for monitoring a patient is provided. A synthesis model is generated in response to 1) data indicative of audio features derived from audio recorded in the patient room, and 2) data indicative of vital signs recorded from the patient monitoring system. Sets of audio parameters indicative of respective plurality of audible alarm settings are then processed according to the synthesis model so as to generate respective outputs, e.g. indicative of audibility of the plurality of alarm sounds according to the audible alarm settings synthesized to be played in or outside the patient room. These outputs can then be presented to a user, so as to allow the user to evaluate e.g. alarm audibility and noise level impact of the plurality of audible alarm settings, and e.g. adjust the settings accordingly, such as alarm thresholds etc.

Abstract: A patient monitor system (10) includes a signal processor (30) which analyzes signals from physiological parameter sensors (20) to derive physiological data values, plots, and alarms. A display (12) displays physiological values and plots (42). An advisor engine, routine, or processor (34) is connected with the signal processor to analyze at least alarm occurrences, also in combination with user interactions, and provide directly actionable advice for reducing alarm frequency which is displayed unobtrusively on the display. The directly actionable advice includes specific actions or adjustments which are specific to a current patient, a present situation, or a present mode or setting of the patient monitor system. The unobtrusively displayed directly actionable advice is displayed without the use requesting it.

Abstract: A method includes obtaining an electrical signal that includes a set of at least two sensed physiologic measurements of a patient, comparing the at least two physiologic measurements with a predetermined physiologic measurement range, identifying data required to determine a probability and a severity of a condition of interest of the patient, in response to determining the at least two physiologic measurements do not satisfy the physiologic measurement range, receiving the identified data in electronic format, determining a first probability and a first severity of the condition of interest based on the received identified data, determining a recommended course of action for the patient based on the first probability and the first severity, resources of a healthcare facility, and an event guideline; and causing a display to visually present the first probability and first severity and the recommended course of action.

Abstract: A medical system (10) and method monitor a patient. Patient data for the patient received. The patient data includes vital sign measurements and laboratory results. A vital signs instability index (VIX) regarding a physiological condition of the patient is calculated from the received vital sign measurements. A laboratory instability index (LIX) regarding the physiological condition is calculated from the received laboratory results. The VIX and the LIX are integrated into an indicator of patient deterioration.

Abstract: A method of monitoring a patient includes receiving patient data from one or more sensors (22) a patient monitoring system (10), comparing the received patient data with preselected thresholds indicative of patient status, determining a patient status from comparing the received patient data with the preselected thresholds, and automatically adjusting a sampling frequency of the one or more sensors (22) based on the determined patient status.

Abstract: A medical system (10) and method monitor a patient. Patient data for the patient received. The patient data includes vital sign measurements and laboratory results. A vital signs instability index (VEX) regarding a physiological condition of the patient is calculated from the received vital sign measurements. A laboratory instability index (LIX) regarding the physiological condition is calculated from the received laboratory results. The VEX and the LIX are integrated into an indicator of patient deterioration.

Abstract: A clinical decision support system (16) monitors one or more patients. The system (16) includes one or more processors (84) programmed to receive patient data for the patients. For each patient, one or more monitoring rules are selected from a plurality of monitoring rules based on patient data availability and/or patient context. A determination is made as to whether a patient is deteriorating using the selected monitoring rules for the patient. In response to determining the patient is deteriorating, an alert is generated.