Abstract: Various embodiments concern video patient monitoring with detection zones. Various embodiments can comprise a camera, a user interface, and a computing system. The computing system can be configured to perform various steps based on reception of a frame from the camera, including: calculate a background luminance of the frame; monitor for a luminance change of a zone as compared to one or more previous frames, the luminance change indicative of patient motion in the zone; and compare the background luminance to an aggregate background luminance, the aggregate background luminance based on the plurality of frames. If the background luminance changed by more than a predetermined amount, then the aggregate background luminance can be set to the background luminance, luminance information of the previous frames can be disregarded, and motion detection can be disregarded.

Abstract: An electronic sitter management system coupled to patient surveillance network having a plurality of video cameras, each camera transmitting a stream of surveillance video of a respective patient room. The sitter management system includes at least one sitter management device and a plurality of sitter devices. Each device being assigned a plurality of patient rooms and capable of receiving a plurality of streams of surveillance video for the corresponding plurality of patient rooms and simultaneously displaying a plurality of video images of the corresponding plurality of patient rooms. Each device is also capable of transmitting sitter device availability information to the sitter management device. The sitter management device being capable of recognizing a sitter device being unavailable and reassigning the plurality of patient rooms previously assigned to the unavailable device to other of the plurality of sitter devices that are available.

Abstract: A system for monitoring a patient in a patient area having one or more detection zones, the system comprising one or more cameras, a user interface, and a computing system configured to receive a chronological series of frames from the one or more cameras, identify liquid candidates by comparing a current frame with a plurality of previous frames of the chronological series, determine locations of the liquid candidates, identify thermal signatures of the liquid candidates, determine types of liquids of the liquid candidates based on the locations and thermal signatures of the liquid candidates, and generate an alert with the user interface corresponding to the determined types of liquids.

Abstract: A method and system for detecting a fall risk condition, the system comprising a surveillance camera configured to generate a plurality of frames showing an area in which a patient at risk of falling is being monitored, and a computer system comprising memory and logic circuitry configured to store motion feature patterns that are extracted from video recordings, the motion feature patterns are representative of motion associated with real alarm cases and false-alarm cases of fall events, receive a fall alert from a classifier, determine motion features of one or more frames from the plurality of frames that correspond to the fall alert; compare the motion features of the one or more frames with the motion feature patterns, and determine whether to confirm the fall alert based on the comparison.

Abstract: Various patient monitoring systems can include a sensor configured to collect three dimensional information. The systems can identify a location of a patient support surface based on the three dimensional information. The systems can set a two dimensional planar threshold based on the patient support surface. The systems can identify a patient location above the patient support surface based on the three dimensional information and compare the patient location to the two dimensional planar threshold. Exceeding the threshold can be indicative of a high risk of a patient fall. An alert can be generated based on the threshold being exceeded. The systems can repeat the identification of the patient support surface location and the setting of the threshold to account for changes in the patient area.

Abstract: A video monitoring system captures image frames of a patient in various positions. The captured image frames are analyzed by the system for changes in a patient's position or movement, frames in which the system detects one or both of patient movement and repositioning are retained. The system analyzes an area of interest within each image frame that corresponds to an area in the camera's view field with the patient. Sequential image frames are compared for motion, only frames without motion, where the patient is still, are analyzed.

Abstract: Various embodiments concern a system for monitoring a patient in a bed, the system comprising a camera, a user interface comprising a screen, and a computing system. The computing system can be configured to monitor, with the camera, for motion within each of a plurality of zones, the plurality of zones comprising a one or more inner zones extending adjacent along the bed, one or more outer zones extending adjacent along the one or more inner zones, and one or more end zones. Motion within the inner zones can trigger a fall alert while motion within the outer or end zones can suspend one or more functions to prevent the fall alert from being issued. The end zones can comprise a bottom zone and one or more top zones.

Abstract: The local surveillance sub-system recognizes that a patient medical procedure has or will soon commence by sensing the presence of a healthcare professional in or near the surveillance area, and in response, creates a separate patient medical procedure A/V file for the surveillance data that will be captured. A dedicated procedure remote may be provided for receiving manual interactions from HC professionals present for a procedure or, alternatively, the local surveillance sub-system may autonomously interact with a personal security token device possessed by the HC professional. A procedure data file is also created that holds all of the pertinent information concerning the procedure that is known by the local surveillance sub-system. The patient procedure surveillance A/V file is given a higher priority than ordinary surveillance data captured by the local surveillance sub-system and is then copied to a nonvolatile memory.

Abstract: A method and system for detecting a fall risk condition, the system comprising a surveillance camera configured to generate a plurality of frames showing an area in which a patient at risk of falling is being monitored, and a computer system comprising memory and logic circuitry configured to store motion feature patterns that are extracted from video recordings, the motion feature patterns are representative of motion associated with real alarm cases and false-alarm cases of fall events, receive a fall alert from a classifier, determine motion features of one or more frames from the plurality of frames that correspond to the fall alert; compare the motion features of the one or more frames with the motion feature patterns, and determine whether to confirm the fall alert based on the comparison.

Abstract: A system for monitoring a patient in a patient area having one or more detection zones, the system comprising one or more cameras, a user interface, and a computing system configured to receive a chronological series of frames from the one or more cameras, identify liquid candidates by comparing a current frame with a plurality of previous frames of the chronological series, determine locations of the liquid candidates, identify thermal signatures of the liquid candidates, determine types of liquids of the liquid candidates based on the locations and thermal signatures of the liquid candidates, and generate an alert with the user interface corresponding to the determined types of liquids.

Abstract: A method and system for detecting a fall risk condition, the system comprising a surveillance camera configured to generate a plurality of frames showing an area in which a patient at risk of falling is being monitored, and a computer system comprising memory and logic circuitry configured to store motion feature patterns that are extracted from video recordings, the motion feature patterns are representative of motion associated with real alarm cases and false-alarm cases of fall events, receive a fall alert from a classifier, determine motion features of one or more frames from the plurality of frames that correspond to the fall alert; compare the motion features of the one or more frames with the motion feature patterns, and determine whether to confirm the fall alert based on the comparison.

Abstract: Various patient monitoring systems can include a sensor configured to collect three dimensional information. The systems can identify a location of a patient support surface based on the three dimensional information. The systems can set a two dimensional planar threshold based on the patient support surface. The systems can identify a patient location above the patient support surface based on the three dimensional information and compare the patient location to the two dimensional planar threshold. Exceeding the threshold can be indicative of a high risk of a patient fall. An alert can be generated based on the threshold being exceeded. The systems can repeat the identification of the patient support surface location and the setting of the threshold to account for changes in the patient area.

Abstract: An electronic sitter management system coupled to patient surveillance network having a plurality of video cameras, each camera transmitting a stream of surveillance video of a respective patient room. The sitter management system includes at least one sitter management device and a plurality of sitter devices. Each device being assigned a plurality of patient rooms and capable of receiving a plurality of streams of surveillance video for the corresponding plurality of patient rooms and simultaneously displaying a plurality of video images of the corresponding plurality of patient rooms. Each device is also capable of transmitting sitter device availability information to the sitter management device. The sitter management device being capable of recognizing a sitter device being unavailable and reassigning the plurality of patient rooms previously assigned to the unavailable device to other of the plurality of sitter devices that are available.

Abstract: A system for monitoring a patient in a patient area having one or more detection zones, the system comprising one or more cameras, a user interface, and a computing system configured to receive a chronological series of frames from the one or more cameras, identify liquid candidates by comparing a current frame with a plurality of previous frames of the chronological series, determine locations of the liquid candidates, identify thermal signatures of the liquid candidates, determine types of liquids of the liquid candidates based on the locations and thermal signatures of the liquid candidates, and generate an alert with the user interface corresponding to the determined types of liquids.

Abstract: Various embodiments concern a system for monitoring a patient in a bed, the system comprising a camera, a user interface comprising a screen, and a computing system. The computing system can be configured to monitor, with the camera, for motion within each of a plurality of zones, the plurality of zones comprising a one or more inner zones extending adjacent along the bed, one or more outer zones extending adjacent along the one or more inner zones, and one or more end zones. Motion within the inner zones can trigger a fall alert while motion within the outer or end zones can suspend one or more functions to prevent the fall alert from being issued. The end zones can comprise a bottom zone and one or more top zones.

Abstract: An electronic sitter management system coupled to patient surveillance network having a plurality of video cameras, each camera transmitting a stream of surveillance video of a respective patient room. The sitter management system includes at least one sitter management device and a plurality of sitter devices. Each device being assigned a plurality of patient rooms and capable of receiving a plurality of streams of surveillance video for the corresponding plurality of patient rooms and simultaneously displaying a plurality of video images of the corresponding plurality of patient rooms. Each device is also capable of transmitting sitter device availability information to the sitter management device. The sitter management device being capable of recognizing a sitter device being unavailable and reassigning the plurality of patient rooms previously assigned to the unavailable device to other of the plurality of sitter devices that are available.

Abstract: An electronic sitter management system coupled to patient surveillance network having a plurality of video cameras, each camera transmitting a stream of surveillance video of a respective patient room. The sitter management system includes at least one sitter management device and a plurality of sitter devices. Each device being assigned a plurality of patient rooms and capable of receiving a plurality of streams of surveillance video for the corresponding plurality of patient rooms and simultaneously displaying a plurality of video images of the corresponding plurality of patient rooms. Each device is also capable of transmitting sitter device availability information to the sitter management device. The sitter management device being capable of recognizing a sitter device being unavailable and reassigning the plurality of patient rooms previously assigned to the unavailable device to other of the plurality of sitter devices that are available.

Abstract: Various patient monitoring systems can include a sensor configured to collect three dimensional information. The systems can identify a location of a patient support surface based on the three dimensional information. The systems can set a two dimensional planar threshold based on the patient support surface. The systems can identify a patient location above the patient support surface based on the three dimensional information and compare the patient location to the two dimensional planar threshold. Exceeding the threshold can be indicative of a high risk of a patient fall. An alert can be generated based on the threshold being exceeded. The systems can repeat the identification of the patient support surface location and the setting of the threshold to account for changes in the patient area.

Abstract: A patient fall prediction system receives video image frames from a surveillance camera positioned in a patient's room and analyzes the video image frames for movement that may be a precursor to a patient fall. In set up phase, the viewpoint of the camera is directed at a risk area associated with patient falls, beds, chairs, wheelchairs, etc. A risk area is defined graphically in the viewport. The patient fall prediction system generates a plurality of concurrent motion detection zones that are situated proximate to the graphic markings of the risk areas. These motion detection zones are monitored for changes between video image frames that indicate a movement. The pattern of detections is recorded and compared to a fall movement detection signature. One fall movement detection signature is a sequential detection order from the motion detection zone closest to the risk area in the frames associated with patient falls, to the motion detection zone farthest away from the risk area.

Abstract: A patient fall prediction system receives video image frames from a surveillance camera positioned in a patient's room and analyses the video image frames for movement that may be a precursor to a patient fall. In set up phase, the viewpoint of the camera is directed at a risk area associated with patient falls, beds, chairs, wheelchairs, etc. A risk area is defined graphically in the viewport. The patient fall prediction system generates a plurality of concurrent motion detection zones that are situated proximate to the graphic markings of the risk areas. These motion detection zones are monitored for changes between video image frames that indicate a movement. The pattern of detections is recorded and compared to a fall movement detection signature.