Cerner Innovation, Inc.

Cerner Innovication, Inc.

Neil Kusens

Michael Kusens

A stroke detection system analyzes images of a person's face over time to detect asymmetric changes in the position of certain reference points that are consistent with sagging or drooping that may be symptomatic of a stroke or TIA. On detecting possible symptoms of a stroke or TIA, the system may alert caregivers or others, and log the event in a database. Identifying stroke symptoms automatically may enable more rapid intervention, and identifying TIA symptoms may enable diagnostic and preventative care to reduce the risk of a future stroke.

Methods and systems for detecting stroke symptoms

A prohibited object detection system detects improper use of an object in an area being monitored. An image of an object detected in an area associated with a monitored individual, such as a patient room, is collected, and the system identifies reference points on the object. The system may compare the reference points to reference points of known improper uses of the object. The system may determine whether the detected object in the improper use position is in proximity to at least a portion of the monitored individual or other person within the monitored area. One or more designated recipients may be alerted if the object is in a position consistent with an improper use.

Methods and systems for detecting prohibited objects

An unauthorized visitor system collects an image of a person detected in a room of a patient. The system identifies reference points on the person's face, for example, points along the cheeks, jowls, and/or brow. The system may compare the reference points to reference points of images associated with registered visitors. The system then determines, based on the comparison, if the person is a registered visitor. One or more designated recipients may be alerted if the person is not a registered visitor or if the person breaches a patient identification zone established around a particular patient. The system may also register the person in a database of visitors.

Detecting unauthorized visitors

Systems and methods for reducing the chance that a patient will develop a bedsore may determine whether a caregiver physically approaches a patient and remains in close physical proximity to a patient for a time sufficient to perform a bedsore prevention action. If a planned bedsore prevention action does not appear to be performed, the systems and methods may alert the patient, the caregiver, or others. A determination may be made as to whether the patient's position has changed in a manner consistent with a bedsore prevention action.

Method and system for determining whether a caretaker takes appropriate measures to prevent patient bedsores

A prohibited object detection system detects prohibited objects in an being monitored. An image of an object detected in an area associated with a monitored individual, such as a patient room, is collected, and the system identifies reference points on the object. The system may compare the reference points to reference points of know objects, including objects identified as being prohibited for the monitored individual and/or the facility or area in which the individual is located. The system then determines whether the detected prohibited object is in proximity to the hand of the monitored individual or other person within the monitored area and whether the object is in a position that is consistent with imminent use of the object. One or more designated recipients may be alerted if the object is a prohibited object that is within close proximity and positioned consistently with an imminent use.

Systems and methods allow caregivers, central monitoring, and/or other persons to monitor whether a patient or another person has generated a call, such as an audio call. The systems and methods work by detecting audio within one or more audio detection zones, which are predefined areas surrounding the patient or other person to be monitored. The systems and methods detect when a command/keyword is spoken in the audio detection zone and generate an appropriate alert to an appropriate role.

Methods and systems for audio call detection

A method and system that allows healthcare providers to monitor disabled, elderly or other high-risk individuals to prevent or reduce falls and/or mitigate the impact of a fall by delivering automated notification of 'at risk' behavior and falls by such an individual. Two systems are used to identify patients&#x2014;a skeletal tracking system that identifies patients by biometric indicators and a virtual blob detection system. In the virtual blob system, the monitored individual is virtually represented as a blob object of at least a specific size by a computerized monitoring system, and such system detects and alerts when the blob object enters or crosses into a virtually defined or designated blob detection zone and remains in the zone for at least a predetermined period of time. These systems may be used concurrently and conflicts between the systems may be resolved.

Systems and methods for determining whether an individual enters a prescribed virtual zone using skeletal tracking and 3D blob detection

A system and method for caregivers, central monitoring companies and other persons to monitor whether individuals entering patients' rooms take appropriate steps to mitigate the spread of healthcare associated infections to the patients receiving healthcare services. Though data from one or more of 3D Motion and Sound Sensors, individuals within a room may be tracked within a virtual zone, and the virtual zone may be shift based on the location of the person. It may be determined whether an individual within the virtual zone washed or sanitized his or her hands prior to entering the room or the virtual zone and may notify caregivers or other persons of individuals approaching the virtual zone in general or without completing a health-care associated infection mitigation action.

Method and system for determining whether an individual takes appropriate measures to prevent the spread of healthcare-associated infections

A method and system that allows healthcare providers, hospitals, skilled nursing facilities and other persons to monitor disabled, elderly or other high-risk individuals to prevent or reduce falls and/or mitigate the impact of a fall by delivering automated notification of 'at risk' behavior and falls by such an individual being monitored where assistance is required.

Method for determining whether an individual leaves a prescribed virtual perimeter

Systems and methods allow caregivers, central monitoring, and/or other persons to monitor whether a patient has moved or changed positions sufficient to prevent the patient from developing bedsores or at least reduce the chance of bedsores from developing. The systems and methods work by detecting when a caregiver has entered within a predefined patient or bed zone. The systems and methods detect whether the caregiver remained within the zone for a predetermined time period. If the caregiver fails to remain within the zone for the predetermined time period, an alert is generated as this could indicate that the caregiver was not present long enough with the patient for the patient to sufficiently move or change positions.

Method and system for determining whether a caregiver takes appropriate measures to prevent patient bedsores

Systems and methods are provided that allow caregivers, central monitoring services, and other persons to monitor whether a monitored individual's hands have entered into an area in which the hands are prohibited, such as areas in which the monitored individual may remove or disturb a piece of medical equipment. When the monitored individual's hands do enter the restricted area that is represented by an electronic virtual safety zone, an alert is generated and transmitted to a designated recipient.

Methods and systems for determining whether a monitored individual's hand(s) have entered a virtual safety zone

Systems, methods and media for detecting a seizure use one or more 3D cameras to monitor an individual. The 3D cameras may movements associated with the tonic or clonic phases of a seizure. A detection zone is used to monitor the individual via the one or more 3D cameras. As the individual moves, the detection zone is automatically adjusted such that zone remains around the person. Detected body position and/or movements, including rate of movement and duration of movement, consistent with a seizure may cause the system or media to alert the individual, a central monitoring system, caregivers, and/or others.

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Sherman Oaks, CA, United States of America

Neil Kusens