22results about "Physiological signal biometric patterns" patented technology

The present disclosure provides a task-independent brainprint recognition method based on feature disentanglement by decorrelation. Existing methods fail to mine inherent identity information of a brain, leading to poor robustness of brainprint recognition in a scenario across tasks and difficulty of promotion thereof in practical use. The present disclosure firstly uses two branch networks to perform coarse-grained decomposition of identity information and task related information in an electroencephalogram (EEG). Secondly, in consideration of an influence of a task state on the identity information, a decorrelating method is employed such that the identity information and the task related information are independent as much as possible. Finally, a brainprint feature in the EEG is fully utilized for classification by adversarial self-supervision. The method of the present disclosure is good in performance and capable of realizing efficient task-independent brainprint recognition, and is a brainprint recognition method robustly useful in the real life.

Some methods may involve determining an authentication rule to authenticate a user of a device, wherein the authentication rule includes liveness criteria and authentication criteria. Some methods may involve determining satisfaction of the liveness criteria based on sensor data captured by one or more sensors of the device. Some methods may involve determining user interaction with one or more biometric sensors of the device in accordance with operation parameters specified by the authentication criteria. Some methods may involve, based on the user interaction in accordance with the operation parameters specified by the authentication criteria, providing biometric data obtained from the one or more biometric sensors for authentication.

The object is to appropriately detect a pulse wave even if brightness is changed due to movement of a subject with respect to lighting. When a face gets closer to a camera with a lighting device, brightness increases, and the size of the face on the camera image increases, while to the contrary, when the face moves away from the camera with a lighting device, the brightness reduces, and the area of the face also reduces. Since the brightness and face size have this correlation, a pulse wave detection device 1 detects the face from a frame image and corrects the brightness of the face in accordance with the size of the face surface. The brightness of the face depends on the distance between the lighting and the face, and this is equal to indirect measurement of the distance from the lighting to the face using the size of the face. As described above, a pulse wave detecting device 1 estimates / measures a pulse rate of the subject from a brightness signal after intensity of the brightness of the face photographed on the frame image is corrected using the size of the face, by using the correlation between the size of the face of the subject on the frame image and the change in the brightness.

A technique is provided that is capable of obtaining image data for personal identification clearly in a short time at an arbitrary position in an area region at least about several times greater than a fingertip. In addition, a technique is provided that allows smooth progress of a series of process flow in a reservation site and an electronic commerce site for excellent user experience. An information processing system is provided that includes: an input section having a surface and configured to allow a user to contact or approximate a position specifier to the surface for information input; and a processing section configured to perform processing based on the information input to the input section, wherein the input section includes a position detection mechanism configured to detect a position of the position specifier on the surface and a reading mechanism configured to read biometric information of the user. TED.

Presented herein are methods of authenticating unknown individuals based on changes in spatial properties and directionality of blood flow through blood vessels over time. At a high level, these methods rely on monitoring blood vessel dynamics to identify unknown individuals. For example, an authentication platform can examine digital images of an anatomical region to establish how properties of a vasculature within the anatomical region change due to morphing. Examples of properties include locations, sizes, volumes, and pressures of blood vessels included in the vasculature, as well as velocities and accelerations of blood flow through the vasculature.

An apparatus and method for controlling a camera are provided, the apparatus having an input unit configured to acquire video data from the camera, an image processing unit configured to determine from the acquired video data whether a particular person is alone in a first area monitored by the camera, a control unit configured to generate a control signal for controlling the camera to operate in a first monitoring mode or a second monitoring mode based on a determination by the image processing unit of whether the particular person is alone in the first area monitored by the camera, and an output unit configured to output the control signal to the camera.

The disclosure relates generally to methods and systems for automated personalized de-stressor recommendation based on stressor estimation. Conventional techniques for detecting the stress and the stressors are mostly manual and employ only some of the influencing parameters such as physiological parameters, behavioral parameters, and so on, thus leading to inaccurate detection of stressors. The present disclosure solves the technical problems in the art by detecting the stress using multi-model evaluation design including physiological changes, psychological changes, behavioral changes, environmental changes, and a bio-chemical indicator. Next, the stressors related to stress detection are identified using a large language model (LLM), which correlates with stress patterns to create a personalized model. Then, appropriate de-stressors are recommended using a recommendation lookup table.

A non-contact and non-invasive apparatus and method for monitoring of health characteristics of a user. The apparatus includes one or more cameras and processor for real-time video of the user and for processing at least each frame from the obtained real-time video. One or more facial regions are from each processed frame to extract one or more regions of interest present therein. The extracted regions of interest are at least one image based physiological monitoring model along with one or more Photo plethysmography imaging (iPPG) and Optical Coherence Tomography (OCT) variations to process one or more extracted regions of interest and obtain at least one result indicative of the health characteristics of the of user based on the real-time video by using Convolutional Neural Network algorithm. The method can be implemented as an AI based software or a platform. A report can be generated for warning for any abnormal range.

The disclosure relates generally to methods and systems for automated personalized de-stressor recommendation based on stressor estimation. Conventional techniques for detecting the stress and the stressors are mostly manual and employ only some of the influencing parameters such as physiological parameters, behavioral parameters, and so on, thus leading to inaccurate detection of stressors. The present disclosure solves the technical problems in the art by detecting the stress using multi-model evaluation design including physiological changes, psychological changes, behavioral changes, environmental changes, and a bio-chemical indicator. Next, the stressors related to stress detection are identified using a large language model (LLM), which correlates with stress patterns to create a personalized model. Then, appropriate de-stressors are recommended using a recommendation lookup table.

In a conventional fatigue / stress examination system, the state of autonomic nerves is measured from a subject's electrocardiographic / pulse data, and the degree of fatigue and stress tendency are expressed in numerical values. However, such numerical value data does not reflect a subjective determination result based on the subject's voice or facial expression during questioning or an interview by a doctor, industrial physician, or health nurse, and therefore does not sufficiently reflect the subject's mood (mental conditions).　The present invention provides an information processing system and the like in which not only quantitative data, such as pulse and heartbeat acquired from a pulse meter, but also the results of a stress check and data such as the subject's voice and facial expression image during counseling using a video call are acquired, and values of stress, brain fatigue, and mood levels are calculated from the data and plotted in a three-dimensional space having an X-axis, a Y-axis, and a Z-axis to visualize the subject's mood and the like. Thus, it is possible to analyze the subject's mood with high accuracy.

An ultrasonic fingerprint sensor and ultrasonic fingerprint sensing method, comprising: generating a first ultrasonic wave having a first frequency; receiving a first signal resulting from reflections of the first ultrasonic wave from each of ridges and valleys of a fingerprint; generating a first image based on the first signal; comparing the first image to a registered reference image to produce a match score; and in response to the match score being less than a threshold, generating a second image using a second frequency.

Proposed is an apparatus for performing image-based cardiovascular biometric information estimation. The apparatus includes a memory that stores data for the cardiovascular biometric information estimation, and a processor that estimates cardiovascular biometric information of an object in an image obtained using the data for the cardiovascular biometric information estimation.

An image processing apparatus is configured to determine whether a person in an image is a living body. The image processing apparatus includes a processor, and a memory storing executable instructions which, when executed by the processor, cause the image processing apparatus to perform operations including determining, based on a time-series image acquired during a predetermined time period, a threshold indicating a skin color range, obtaining color information describing a skin color area in the time-series image based on the threshold, and controlling, based on the color information, whether to continue biometric determination processing for determining whether a person in the time-series image is a living body.

The application discloses a task-independent brainprint recognition method based on feature decoupling. The existing method lacks the mining of inherent identity information of the brain, which leads to poor robustness of brainprint recognition in a cross-task scene, and is difficult to popularize in practical application. The application first adopts two branch networks to respectively coarsely decompose identity information and task-related information in electroencephalogram (EEG); secondly, considering the influence of the task state on the identity information, a decoupling method is adopted to make the identity information and the task-related information as independent as possible; finally, the brainprint features in the EEG are fully utilized for classification in an adversarial self-supervised manner. The method has good performance, can realize efficient task-independent brainprint recognition, and is a brainprint recognition method which can be robustly used in real life.

Control device for a vehicle (10; 100) with an internal combustion engine (12), with an automatic transmission (40; 106) which forms part of an energy transmission path between the internal combustion engine (12) and a drive wheel (14), and with a rotary device (MG2) which is coupled to the drive wheel (14) to transmit drive energy, wherein the control device has an electronic control unit (90) which is configured to: a driver assistance control system for driving the vehicle (10, 100) at least by automatically controlling a vehicle speed independently of any driving action by a driver; to perform regenerative braking using the rotary device (MG2) at a time of deceleration while driving with the driver assistance control and to limit downshifting of the automatic transmission (40, 106) when a requested deceleration amount (Grdem) for the vehicle (10, 100) is equal to or less than a predetermined deceleration amount (Grf); and to perform regenerative braking using the rotary device (MG2) at the time of deceleration while driving with the driver assistance control and not to restrict downshifting if the required deceleration amount (Grdem) is higher than the predetermined deceleration amount (Grf), wherein the electronic control unit (90) is configured to perform a shift depending on whether downshifting is to be limited on the basis of the requested deceleration amount (Grdem), if a second requested deceleration amount for the vehicle (10, 100) associated with an operation by the driver is not included in the requested deceleration amount (Grdem) during driving with the driver assistance control, the required deceleration amount (Grdem) is a deceleration amount (Gr) achievable by regenerative braking and by engine braking using the friction of the internal combustion engine (12); and the electronic control unit (90) is configured to set the requested deceleration amount (Grdem) equal to or lower than the predetermined deceleration amount (Grf) when the deceleration amount (Gr) is increased by a wheel brake in a state where the requested deceleration amount (Grdem) is higher than the predetermined deceleration amount (Grf) at the time of deceleration during driving with the driver assistance control.

Method comprising: - Obtaining two or more biometric user pulse data from two or more measurement points, each measurement point being located at a different body location of a user, using one or more pulse sensors; - Transforming the two or more biometric user pulse data into the user's biometric signature data, wherein the transformation includes correlating the two or more biometric user pulse data; and - Identifying, using a processor, the user based on the biometric user signature data.

Optical sensing apparatus includes a transmitter, which transmits outgoing FM coherent optical radiation toward a target scene, and a receiver, including an array of detectors, which output electrical signals in response to photons that are incident on the detectors, and optics to image the target scene onto the array while diverting a part of the outgoing FM coherent optical radiation to form a local beam, which mixes with incoming optical radiation from the target scene. Processing circuitry processes the electrical signals output by the detectors to produce a 2D image of the target scene, to identify an object of interest in the 2D image, which is imaged onto an area within the array, to extract beat frequencies in response to the mixed optical radiation from the electrical signals output by the detectors in the area, and to measure a feature of the object of interest responsively to the beat frequencies.

A device for estimating cardiovascular biometric information based on an image is presented according to one embodiment of the present invention. The device may comprise: a memory for storing data for estimation of the cardiovascular biometric information; and a processor for estimating cardiovascular biometric information for an object in an image obtained using the data for estimation of the cardiovascular biometric information.

This invention relates to a high-concurrency real-time face detection method and system based on multi-GPU collaboration, belonging to the field of computer vision technology. It includes the following steps: concurrently pulling real-time video streams from multiple cameras via the RTSP protocol, and implementing heartbeat detection and automatic reconnection after disconnection using a state machine connection management mechanism; performing motion pre-filtering on decoded video frames, discarding frames with a difference ratio below a threshold; serializing qualified frames and their metadata and writing them into a persistent message queue supporting consumer groups. Based on the GPU memory capacity of the computing nodes, an appropriate number of inference worker processes are dynamically started. Each process preemptively reads video frames from the queue, performs face detection using a TensorRT-accelerated deep learning model, and then filters and classifies high-quality faces through multi-dimensional quality assessment. This invention can improve the efficiency and accuracy of face detection.

The invention relates to a method for authenticating a person (224). The method comprises: - providing (102) a display device (216); - providing (103) a contactless sensor of brain activity - hereinafter referred to as a KLHA sensor (218); - displaying (104) several facial images (208-214, 304, 404, 504) of different persons to the one person (224), wherein the facial images comprise one or more self-images (304, 404, 504) of the one person and one or more images of others;- while the multiple facial images of one person are displayed, recording (106) of first (708, 712) and second (704, 706, 710) brain activity signals by the KLHA sensor, wherein the first brain activity signals are recorded while this one person is shown the one or more self-images (304, 404, 504), and wherein the second brain activity signals are recorded while this one person is shown the one or more other person images (208-214); - analysis (108) of the recorded brain activity signals to authenticate the one person to an authentication software.;

A method for providing a comparison data set includes providing a time-resolved first data set including a plurality of first data points that have time intensity curves of a first contrast agent flow in a region of interest in a first time period, providing a time-resolved second data set including a plurality of data points that have time intensity curves of a second contrast agent flow in the region of interest in a second time period, and spatially and temporally registering the first data set and the second data set. The areas of the region of interest that are mapped in the data sets are classified into contrasted vessel segments and tissue region. A deviation between the tissue regions of the data sets is identified by comparison of the time intensity curves, and the comparison data set is provided based on the registered first and second data sets. The comparison data set contains at least one parameter characterizing the deviation.