Abstract: A first behaviometric user profile for a first user is generated and stored, by detecting a position and velocity of the first user relative to the mobile device based on a received response from a radar transmission while the first user uses the mobile device, the received response over time indicating a position and velocity of the first user. Based on further received responses of additional radar transmissions an additional behavioral pattern of an unknown user is determined. The additional behavioral pattern is then compared to the first behaviometric user profile, and based on the comparison, a measure of similarity between the first behaviometric user profile and the additional behavioral pattern, measuring if the first user and the unknown user are a same user is heuristically determined. As a result of the comparison, operation or access to at least some data stored on the mobile device is prevented.

Abstract: A foldable display device according to the present disclosure includes a display panel including a display area and a non-display area, a touch panel disposed on the display panel and including a bridge electrode, a plurality of insulating layers, a first touch electrode, and a second touch electrode. The device includes a plurality of crack stoppers disposed in the non-display area of the touch panel and configured by patterning the insulating layers and an adhesive layer. The adhesive layer fills a space between the plurality of crack stoppers from which the insulating layers are removed, and is disposed between the display panel and the touch panel. Accordingly, crack occurrence may be suppressed even if a folding/unfolding operation of the foldable display device is repeated. Thus, crack occurrence in the foldable display device may be improved and at the same time, folding characteristics may increase.

Abstract: A remote control that receives state information from an associated media device is disclosed. The remote control, in response to receiving data indicating that the media device is in a content state, may update an input assembly to indicate that the assembly may be used to perform a movement function. The remote control may instruct the media device to perform a movement function in response to a selection gesture, where the degree of movement is a single unit. In response to a swipe gesture, the remote control may instruct the media device to perform a linear movement with a greater degree of movement. Buttons and functions of the remote control may be further adapted in response to a menu-based state, or other states of the media device.

Abstract: Disclosed herein are systems and methods for controlling electronic devices based on detected brain activity. For example, a system includes a wearable over-the-ear electronic device has a set of dry EEG sensors, a camera, a processor, and programming instructions. The programming instructions cause the processor to receive images from the camera, process the images to identify features corresponding to a known device, and receive brain-wave signals from the EEG sensors. The system compares the brain-wave signals to measure a level of brain activity. Upon detection of both (a) a feature corresponding to the known device and (b) a level of brain activity that deviates from a baseline by at least a threshold level, the system generates a command signal configured to cause the known device to actuate and transmits the command signal to a controller for the known device.

Abstract: A panel control circuit for controlling a display panel comprising a first data line and a second data line includes a timing controller configured to generate input data comprising a first input data and a second input data, a first driving circuit configured to output a first video signal corresponding to the first input data into the first data line, and a second driving circuit configured to output a second video signal corresponding to the second input data into the second data line, wherein the timing controller is configured to turn off the second driving circuit based on a first deviation, a second deviation, or a third deviation.

Abstract: Gesture-informed patient management systems and related medical devices and operating methods are provided. A method of assisting operation of a medical device using a sensing arrangement capable of detecting physical movement by a user involves detecting a configuration procedure performed by the user in response to output of the sensing arrangement indicative of one or more gestures with respect to the medical device by the user, determining a current state of the user within the configuration procedure based at least in part on the one or more gestures with respect to the medical device relative to a sequence of gestures corresponding to a defined sequence of tasks for the configuration procedure, and providing a graphical user interface display on a client device comprising guidance information influenced by the current state within the configuration procedure.

Abstract: Techniques for performing gesture recognition with an electronic device are disclosed where the electronic device has a wireless communications capability using beamforming techniques and includes a plurality of millimeter wave antenna modules, each antenna module including at least one transmit antenna and at least one receive antenna, the antennas being operable in one or more frequency ranges greater than 20 GHz. Performing gesture recognition includes: simultaneous operation of the at least one transmit antenna and the at least one receive antenna so as to provide a radar capability; and detecting a presence and motion of a reflective object by analyzing magnitude and phase of signals received by the at least one receive antenna and resulting from reflection of signals transmitted by the transmit antenna and reflected by the reflective object.

Abstract: A method for determining an electronic device, a system for determining an electronic device, a computer system, and a computer-readable storage medium, the method includes: acquiring a recognition result by recognizing a first action performed by an operating object through a first electronic device (S201); and determining a second electronic device which is controllable by the first electronic device according to the recognition result (S202).

Abstract: A power supply time sequence control circuit and a control method thereof, a display driver circuit, and a display device. The power supply time sequence control circuit includes: a delay control sub-circuit, a delay detection sub-circuit and an output sub-circuit. The delay control sub-circuit is configured to receive a first voltage outputted by the first input voltage terminal and to output the first voltage after delaying for a pre-determined time period; the delay detection sub-circuit is configured to send a trigger signal to the output sub-circuit upon the first voltage being received by the delay detection sub-circuit; the output sub-circuit is configured to be in an on-state in response to the trigger signal, so as to output the first voltage provided by the first input voltage terminal to the signal output terminal, and to enable the signal output terminal to output the first voltage.

Abstract: A method for automatic gesture recognition in which, by a machine learner data of a respective gesture of a variety of gestures executed by a user and captured by at least one sensor gestures of a class are assigned to a variety of predetermined classes, and in which the machine learner is trained with a training data set, which is divided into predetermined data segments. The respective data segments are data segments of the training data set are assigned to the variety of predetermined classes by means of the machine learner. A respective contribution, with the respective assignment processes for the assignment of respective data segments are incorporated into the automatic gesture recognition of a particular class.

Abstract: A gesture recognition device and method using radar are proposed. The gesture recognition device includes: a signal receiving unit for receiving a radar signal reflected by a gesture of a user; a clutter removing unit for removing clutter from the signal received by the signal receiving unit; and a signal magnitude variance acquiring unit for acquiring the variance of a signal magnitude from a reflection signal from which the clutter has been removed. The proposed device and method have an advantage of enabling a gesture to be recognized with performance that is robust to changes in distance and direction between a user and a radar sensor.

Abstract: A computer controller when in a normal orientation causes a first context of simulation play to be implemented. When inverted, the controller causes a second, different context of simulation play to be implemented.

Abstract: This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor (108) and/or a movement sensor (108) produces a context of a user equipment (102). The techniques and systems enable the user equipment (102) to recognize contexts when a radar system (104) can be unreliable and should not be used for gesture-recognition, enabling the user equipment (102) to automatically disable or “gate” the output from the radar system (104) according to context. The user equipment (102) prevents the radar system (104) from transitioning to a high-power state (1910) to perform gesture-recognition in contexts where radar data detected by the radar system (104) is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Abstract: A method includes receiving from a transceiver, at a processor of an electronic device, a radar signal, the radar signal including a set of signal strength values across a range of Doppler frequency shift values and a range of time values. The method further includes extracting a time series of frequency features from the radar signal, wherein frequency features of the time series of frequency features include a determined Doppler frequency shift value for each time value of the range of time values, identifying segments within the time series of frequency features, analyzing the segments to determine a start time for a classification engine, at the start time, analyzing, by the classification engine, at least one of a subset of the time series of frequency features or a subset of the radar signal to identify a control gesture, and triggering a control input associated with the control gesture.

Abstract: An input sensing device includes an input sensing panel, a flexible circuit board connected to a first side of the input sensing panel, a first lower protective film below the input sensing panel, a second lower protective film below the first lower protective film, and a reinforcing member between a lower portion of the flexible circuit board and a second side of the input sensing panel that is adjacent to the first side, the reinforcing member covering a portion of the lower portion of the flexible circuit board. A side facing the reinforcing member of any one of the first lower protective film and the second lower protective film is spaced from the reinforcing member.

Abstract: Systems and methods associated with determining a pointing target of pointing device are disclosed. One embodiment disclosed herein is a method conducted with a control device having a pointing direction and an onboard imager. The field of view of the onboard imager includes the pointing direction. The method includes capturing a reference image, determining a characteristic quantity based on the reference image, generating a feedback message based on the characteristic quantity, and predicating a setup phase termination for the control device on the characteristic quantity.

Abstract: A system for recognizing gestures generates a skeletal model from video data of a subject. A defined subset of attributes of the skeletal model are mapped to defined positions of a vector. A gesture is recognized by evaluating a neural network using the vector as input. The neural network, trained using training vectors generated according to the definitions of skeletal model attributes and vector positions, classifies a gesture based on the input vector.

Abstract: A mobile computing device for measuring self-awareness of a user includes motion sensors and a processor for displaying instructions on how to conduct a whipping gesture, executing a body awareness assessment including receiving sensor data while the user performs multiple whipping gestures, executing an emotional awareness assessment including receiving sensor data while the user performs multiple whipping gestures, executing a self-assessment including receiving sensor data while the user performs multiple whipping gestures, executing a resiliency awareness assessment including receiving a response from the user to a question and generating a final self-awareness score corresponding to the user's self-awareness based on the body awareness assessment, emotional awareness assessment, self-assessment and resiliency awareness assessment.

Abstract: An input device includes an enclosure defining a three-dimensional input space and one or more self-mixing interferometry sensors coupled to the enclosure and configured to produce a self-mixing interferometry signal resulting from reflection of backscatter of emitted light by a body part in the three-dimensional input space. In various examples, movement of the body part may be determined using the self-mixing interferometry signal, which may in turn be used to determine an input. In some examples, a body part displacement or a body part speed and an absolute distance to the body part may be determined using the self-mixing interferometry signal and used to determine an input. In a number of examples, multiple self-mixing interferometry sensors may be used and the movement may be determined by analyzing differences between the respective produced self-mixing interferometry signals.

Abstract: An integrated functional multilayer structure includes a flexible, 3D-formable substrate film having a first surface facing towards an environment of the structure and a user therein, and an opposite second surface facing towards the internals of the structure, wherein the first and second surfaces and remaining material of the substrate film in between locally define a three-dimensional protrusion extending from a plane of surrounding substrate film material and formed from locally stretched and shaped material of the substrate film, side walls perceptible by touch; circuitry provided upon the substrate film includes a number of conductive traces, electrodes and/or components to detect touch on two or more of the plurality of side walls and at least one fill layer upon the substrate film to at least partially embed the circuitry.