A notification control device for controlling notification based on subject information is disclosed. The subject information including temperature image data, which indicates temperature of a subject captured within a predetermined capturing range, is received. A predetermined destination of notification information, which represents a state of the subject based on the subject information, is notified. A process of notifying the notification information to the predetermined destination is stopped depending on whether or not the subject information includes predetermined identification information.

A method for navigational assistance for the visually impaired can include determining that an image captured by an imaging device contains an unknown object and determining that the unknown object is not resolvable within a threshold period of time. The method can further include performing an operation to reallocate computing resources between memory devices couplable to the imagining device in response to determining that the unknown object is not resolvable within the threshold period of time. Data corresponding to the unknown object can be written to the reallocated computing resources and an operation involving the data corresponding to the unknown object can be performed to resolve the unknown object using the reallocated computing resources.

A method for influencing a system for monitoring alertness of an operator when operating a device includes providing one or more representations of features of the operator in a detection region of the system, where each of the one or more representations reproduces at least one feature of the operator and where the influencing is based on the detection of the one or more representations by the system.

A robot in a location interacts with a user. The robot includes a camera, an image recognition processor, a microphone and a loudspeaker, a voice assistant, and a wireless transceiver. The robot moves around and creates a model of the location, and recognizes changes. It recognizes objects of interest, beings, and situations. The robot monitors the user and recognizes body language and gesture commands, as well as voice commands. The robot communicates with the user, the TV, and other devices. It may include environment sensors and health status sensors. It acts as a user companion by answering queries, executing commands, and issuing reminders. It may monitor to determine if the user is well. The robot may monitor objects of interest, their placement and their status. When necessary, it communicates with the user.

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.

A method and system for detecting a person falling, confirming a potential fall, and taking action to mitigate the effects of a fall.

An embodiment in accordance with the present invention includes a technology to continuously measure patient mobility automatically, using sensors that capture color and depth images along with algorithms that process the data and analyze the activities of the patients and providers to assess the highest level of mobility of the patient. An algorithm according to the present invention employs the following five steps: 1) analyze individual images to locate the regions containing every person in the scene (Person Localization), 2) for each person region, assign an identity to distinguish ‘patient’ vs. ‘not patient’ (Patient Identification), 3) determine the pose of the patient, with the help of contextual information (Patient Pose Classification and Context Detection), 4) measure the degree of motion of the patient (Motion Analysis), and 5) infer the highest mobility level of the patient using the combination of pose and motion characteristics (Mobility Classification).

A monitoring system includes a sensor data acquisition device configured to acquire information on an activity of a user; a data analyzer configured to analyze the acquired information on the activity of the user and detect occurrence of an abnormality in the activity of the user; an imaging controller configured to instruct an imaging terminal device that captures an image of the activity of the user to start capturing an image of the user and record imaging data in a case where the occurrence of the abnormality is detected by the data analyzer; an imaging data acquisition device configured to acquire the imaging data recorded by the imaging terminal device; a data storage device configured to store the imaging data acquired by the imaging data acquisition device; and an output device configured to output the imaging data.

Systems and methods for identifying a condition associated with an individual in a home environment are provided. Sensors associated with the home environment detect data, which is captured and analyzed by a local or remote processor to identify the condition. In some instances, the sensors are configured to capture data indicative of electricity use by devices associated with the home environment, including, e.g., which devices are using electricity, what date/time electricity is used by each device, how long each device uses electricity, and/or the power source for the electricity used by each device. The processor analyzes the captured data to identify any abnormalities or anomalies, and, based upon any identified abnormalities or anomalies, the processor determines a condition (e.g., a medical condition) associated with an individual in the home environment. The processor generates and transmits a notification indicating the condition associated with the individual to a caregiver of the individual.

A system and a method for predicting kinesthetic outcomes from observed position, posture, behavior or activity of an individual 1602, 1702. The system uses kinesthetic activity sensors 102, 104 each collecting one or more of audio, video, or physiological signals and capturing the activity of the individual or an ambient environment of the individual. These signals are delivered into a computer system 106 implementing a learning routine 108 which constructs one or more personalized kinetic state models 1510 of positional states for the individual and transitions between the positional states, and further develops one or more customized multi-dimensional prediction models 1500 for the individual and uses the multidimensional prediction models to predict behaviors, activities and/or positional changes likely to occur in the future, and provides notice of predicted unsafe or undesired outcomes.