A dynamic anatomic atlas is disclosed, comprising static atlas data describing atlas segments and dynamic atlas data comprising information on a dynamic property which information is respectively linked to the atlas segments.

A vehicle includes a processing device that detects an authentication device approaching the vehicle, determines a user's impaired state based on user condition information acquired using at least one device mounted on the vehicle, and performs a safe driving assistance service. The safe driving assistance service can prevent an impaired user from operating the vehicle.

A system and a method are described for monitoring a medical care environment. In one or more implementations, a method includes identifying a first subset of pixels within a field of view of a camera as representing a bed. The method also includes identifying a second subset of pixels within the field of view of the camera as representing an object (e.g., a subject, such as a patient, medical personnel; bed; chair; patient tray; medical equipment; etc.) proximal to the bed. The method also includes determining an orientation of the object within the bed.

Methods, systems, and computer-program products used for assessing athletic ability and generating performance data. In one embodiment, athlete performance data is generated through computer-vision analysis of video of an athletic performing, e.g., during practice or gameplay. The generated performance data for the athlete may include, for example, maximum speed, maximum acceleration, time to maximum speed, transition time (e.g., time to change direction), closing speed (e.g., time to close the distance to another athlete), average separation (e.g., between the athlete and another athlete), play-making ability, athleticism (e.g., a weighted computation and/or combination of multiple metrics), and/or other performance data. This performance data may be used to generate and/or update a profile associated with the athlete, which can be utilized for recruiting, scouting, comparing, and/or assessing athletes with greater efficiency and precision.

A headset comprise a frame and a vibration sensor coupled to the frame. The vibration sensor may be located in a nosepad of the frame, and configured to measure tissue vibrations of a user when the headset of worn by the user. A controller receives a signal corresponding to the measured vibration data from the vibration sensor, and analyzes the received signal to infer a sequence of states of the received signal, such as a sequence of respiratory states. The controller further determines a value of a health metric based upon the inferred sequence of states, e.g., a respiratory rate of the user, and performs an action using the determined value of the health metric.

Various techniques are disclosed to provide for improved detection of elevated human body temperatures. In one example, a method includes receiving a thermal image. The method also includes processing the thermal image to detect a person's face and a characteristic associated with the person. The method also includes selecting a circadian rhythm model associated with the detected characteristic.

The method also includes determining an expected body temperature using the circadian rhythm model. The method also includes extracting a temperature associated with the person's face from the thermal image. The method also includes comparing the extracted temperature with the expected body temperature to detect an elevated body temperature condition. Additional methods and systems are also provided.

A gait motion display system including: a triaxial accelerometer, attached to the subject, that measures acceleration data of a subject in walking; an imaging unit that takes images of the subject in walking to obtain moving image data showing gait motions of the subject; a recording unit that records the acceleration data and the moving image data in synchronization with each other; an identification unit that converts the acceleration data recorded by the recording unit into horizontal displacement data and vertical displacement data, and identifies, from the moving image data, a representative image corresponding to a representative motion in a gait cycle, based on the horizontal displacement data or the vertical displacement data; and a display that displays an image illustration of the representative motion in the gait cycle, with the representative image identified by the identification unit.

Certain aspects of the disclosure are directed to an apparatus including a scale and external circuitry. The scale includes a platform, and data-procurement circuitry for collecting signals indicative of the user's identity and cardio-physiological measurements. The scale includes processing circuitry to process data obtained by the data-procurement circuitry, therefrom generate cardio-related physiologic data, and to send user data to the external circuitry. The external circuitry identifies a risk that the user has a condition based on the reference information and the user data provided by the scale and outputs generic information correlating to the condition to the scale that is tailored based on the identified risk.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

Systems and methods are disclosed to objectively identify sub-second behavioral modules in the three-dimensional (3D) video data that represents the motion of a subject. Defining behavioral modules based upon structure in the 3D video data itself—rather than using a priori definitions for what should constitute a measurable unit of action—identifies a previously-unexplored sub-second regularity that defines a timescale upon which behavior is organized, yields important information about the components and structure of behavior, offers insight into the nature of behavioral change in the subject, and enables objective discovery of subtle alterations in patterned action. The systems and methods of the invention can be applied to drug or gene therapy classification, drug or gene therapy screening, disease study including early detection of the onset of a disease, toxicology research, side-effect study, learning and memory process study, anxiety study, and analysis in consumer behavior.