An example method includes causing a light projecting system of a distance sensor to project a three-dimensional pattern of light onto an object, wherein the three-dimensional pattern of light comprises a plurality of points of light that collectively forms the pattern, causing a light receiving system of the distance sensor to acquire an image of the three-dimensional pattern of light projected onto the object, causing the light receiving system to acquire a two-dimensional image of the object, detecting a feature point in the two-dimensional image of the object, identifying an interpolation area for the feature point, and computing three-dimensional coordinates for the feature point by interpolating using three-dimensional coordinates of two points of the plurality of points that are within the interpolation area.

A sports training aid comprising a body unit, attachable to a person's body or the person's sports implement, is provided with a positioning sensor module; a feedback stimulator; and a processor. The sports training aid is configured to provide instantaneous feedback on motion faults of a studied sports motion, and the body unit is intended to be attached to a person's body (or a person's sports implement) at a representative location, the location being bound to travel a path representative of the studied sports motion, and the positioning sensor module comprises acceleration sensors and gyro sensors. The processor is configured to determine a still position corresponding to an event wherein the body unit is determined to be still, to keep track of the sensor module's movements relative to the still position, and to activate the feedback stimulator in real time, upon detection of a sports motion fault.

A system that measures a swing of equipment (such as a bat or golf club) with inertial sensors, and analyzes sensor data to create a rotational profile. Swing analysis may use a two-lever model, with a body lever from the center of rotation to the hands, and an equipment lever from the hands to the sweet spot of the equipment. The rotational profile may include graphs of rates of change of the angle of the body lever and of the relative angle between the body lever and the equipment lever, and a graph of the centripetal acceleration of the equipment. These three graphs may provide insight into players' relative performance. The timing and sequencing of swing stages may be analyzed by partitioning the swing into four phases: load, accelerate, peak, and transfer. Swing metrics may be calculated from the centripetal acceleration curve and the equipment/body rotation rate curves.

A recording apparatus includes: a captured data acquisition unit configured to acquire captured data captured by a camera that captures an image of an outside of a vehicle; an event detection unit configured to detect an event with respect to the vehicle; an attachment/detachment detection unit configured to detect an attachment/detachment state of the recording apparatus with respect to the vehicle; and a recording controller configured to store, when the event detection unit has detected the event, captured data for a predetermined period of time due to the detected event as first event recording data, invalidate, when it is detected by the attachment/detachment detection unit that the recording apparatus has been detached from the vehicle, the detection of the event by the event detection unit after the detection of the detachment, and store captured data after the detection of the detachment as second event recording data.

Systems and methods for eye image set selection, eye image collection, and eye image combination are described. Embodiments of the systems and methods for eye image set selection can include comparing a determined image quality metric with an image quality threshold to identify an eye image passing an image quality threshold, and selecting, from a plurality of eye images, a set of eye images that passes the image quality threshold.

Systems and methods for eye image set selection, eye image collection, and eye image combination are described. Embodiments of the systems and methods for eye image set selection can include comparing a determined image quality metric with an image quality threshold to identify an eye image passing an image quality threshold, and selecting, from a plurality of eye images, a set of eye images that passes the image quality threshold.

A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

A radar detection method may include: transmitting a first radar signal in a field of view and receiving a second radar signal originated from reflections of the first radar signal in the field of view; generating a detection profile by processing the first and second radar signals, the detection profile representing intensities of the second radar signal as a function of positions in the field of view; and analyzing the detection profile to identify targets in the field of view. Analyzing the detection profile may include: using a first mode of analysis, with lower sensitivity, for first cycles, wherein the first mode of analysis is configured to detect a target entering the field of view; using a second mode of analysis, with higher sensitivity, for second cycles following the first cycles, wherein the second mode of analysis is configured to detect stay of the target in the field of view.

A radar detection method may include: transmitting a first radar signal in a field of view and receiving a second radar signal originated from reflections of the first radar signal in the field of view; generating a detection profile by processing the first and second radar signals, the detection profile representing intensities of the second radar signal as a function of positions in the field of view; and analyzing the detection profile to identify targets in the field of view. Analyzing the detection profile may include: using a first mode of analysis, with lower sensitivity, for first cycles, wherein the first mode of analysis is configured to detect a target entering the field of view; using a second mode of analysis, with higher sensitivity, for second cycles following the first cycles, wherein the second mode of analysis is configured to detect stay of the target in the field of view.

A system for authenticating a user attempting to access a computing device or a software application executing thereon. A data storage device stores one or more digital images or frames of video of face(s) of authorized user(s) of the device. The system subsequently receives from a first video camera one or more digital images or frames of video of a face of the user attempting to access the device and compares the image of the face of the user attempting to access the device with the stored image of the face of the authorized user of the device. To ensure the received video of the face of the user attempting to access the device is a real-time video of that user, and not a forgery, the system further receives a first photoplethysmogram (PPG) obtained from a first body part (e.g., a face) of the user attempting to access the device, receives a second PPG obtained from a second body part (e.g., a fingertip) of the user attempting to access the device, and compares the first PPG with the second PPG. The system authenticates the user attempting to access the device based on a successful comparison of (e.g., correlation between, consistency of) the first PPG and the second PPG and based on a successful comparison of the image of the face of the user attempting to access the device with the stored image of the face of the authorized user of the device.