605 results about "Biometric data" patented technology

According to various embodiments, a system and method for verifying a user's identity using both document-based and biometric data is disclosed. The system may prompt a user to upload an image of a government-issued identification document and extract user information from the image using optical character recognition (OCR). The system may also extract the embedded face image from the ID and prompt the user to take a real-time selfie while performing one or more randomized actions or poses. A facial recognition engine may compare the extracted ID image to the live selfie to determine a similarity score. Based on this match, along with optional document authenticity checks, the system may confirm the user's identity in real-time for use cases such as account access, onboarding, and regulatory KYC compliance.

Examples relate to a fatigue detection system to monitor and assess pilot fatigue levels during flight operations. An example system includes a wearable biometric sensor (WBS) integrated into a wristband that captures biometric data from the pilot. A processor analyzes the captured data to determine the pilot's fatigue level. When this level exceeds a predetermined threshold, the system provides an alert to the pilot through a haptic feedback mechanism in the wristband. Additionally, the system generates personalized fatigue mitigation advice, which is displayed on an electronic flight bag (EFB) application accessible to the pilot. The advice may include recommendations for taking a controlled rest, consuming caffeine, or engaging in physical activity. The system enhances flight safety by providing real-time alerts and actionable advice to combat pilot fatigue.

A system and method for generating patient care instructions based on real-time sensor and medical data. The method includes receiving time-stamped sensor data from a sensor network comprising motion, occupancy, and environmental sensors, and receiving medical data associated with a patient, including medical conditions, treatment history, medication data, and biometric data. The sensor data is enriched with room-specific information, and activity pattern data is generated in real time using a pattern recognition model. The activity pattern data includes mobility, sleep patterns, medication adherence, statistical measures, temporal patterns, and correlations with medical data. Anomalies indicating potential health risks are detected by comparing current activity patterns with baseline data. A prediction model, trained on historical patient data, assesses the patient's health and generates care instructions accordingly. The care instructions are securely delivered to patient devices, caregiver applications, or automated medication dispensing systems, enabling timely interventions and continuous patient monitoring.

Systems and methods for performing zero knowledge proofs to prove a user's possession of secret data and / or biometric data without exposing such data. The methods can include receiving a certificate signing request and biometric data associated with a user; creating a stable key based at least in part on the biometric data; creating a private key based at least in part on the stable key; transmitting the private key to the user device for local storage thereon; creating a public key based at least in part on the private key; and forwarding the certificate signing request to an issuer.

The invention relates to the technical field of artificial intelligence and biological characteristic analysis, in particular to an AI-based personalized postpartum rehabilitation medical beauty evaluation system and method. The method comprises the following steps: generating a standardized action sequence according to a rehabilitation stage and a historical record of a user and guiding execution; collecting dynamic biological characteristic data in real time; aligning data and distributing dynamic weights by using a multi-modal fusion model guided by time sequence semantics, constructing a three-dimensional response graph by combining a tension response function, a collaborative exponential function and a stable fluctuation function, and generating individual embedded vectors through a graph neural network; identifying a potential high-risk time period through map potential energy offset analysis and disturbance sensitivity factors; integrating a user state, a historical response and an intervention knowledge graph, recommending a dynamically adaptive intervention scheme by using a multi-channel attention network, and continuously optimizing through a feedback closed loop; precise evaluation and personalized intervention recommendation of the postpartum rehabilitation process are realized through multi-modal fusion and dynamic modeling, and the rehabilitation efficiency and safety are improved.

The invention relates to the technical field of additive manufacturing, and discloses an additive manufacturing lens surface optimization method based on real-time feedback control. The method comprises the following steps: firstly, acquiring eye biometric data and personalized visual demand parameters of a wearer, establishing a personalized optical model of eyeballs according to the eye biometric data and the personalized visual demand parameters, and deducing a retina defocusing amount distribution map; and determining spatial arrangement and geometric morphology parameters of the distributed out-of-focus microstructure layer on the lens according to the atlas. In the additive manufacturing process, the optical material is deposited and solidified layer by layer, and the three-dimensional shape information of the surface of the optical material is obtained in real time after deposition of each layer. And comparing and analyzing the morphology information with a theoretical model to generate a morphology deviation result. And then, a correction instruction of the printing parameters is calculated by using the correction model, and the printing parameters of the additive manufacturing equipment are adjusted in real time, so that real-time compensation and optimization of the morphology deviation are realized, and finally, a high-precision lens product meeting personalized optical design requirements is manufactured.

Methods and apparatus for biometric data maintenance, access and distribution across two or more experiential and / or network domains. In one embodiment, a 5G NR-based network architecture is provided which allows ultra-low latency and effectively user-imperceptible biometric data use for e.g., authentication and maintenance of user state across multiple domains via multiple constituent user devices (e.g., UEs). The network architecture includes both (i) a distributed biometric database (BDB) model wherein relevant biometric data for individuals / UEs is intelligently cached in various portions of the distributed database, and (ii) centralized and local BAEs (biometric analytics entities) which manage the aforementioned intelligent caching, as well as network configuration using one or both of 5G NR network “slicing” and CU / DU split options to optimize end-user biometric-related applications such as those providing identification / authentication, AR functions, VR functions or yet others.

The present disclosure relates generally to implementing biometric authentication, including providing user interfaces for: while the electronic device is in a first state in which a respective function of the electronic device is disabled, detecting one or more activations of the button; and in response to detecting the one or more activations of the button: capturing, with the one or more biometric sensors that are separate from the button, biometric data; if the biometric data satisfies biometric authentication criteria, transitioning the electronic device to a second state in which the respective function of the electronic device is enabled; and if the biometric data does not satisfy the biometric authentication criteria, maintaining the electronic device in the first state and displaying, on the display, an indication that biometric authentication has failed.

A computer-implemented method of registering a user identifier in a public key infrastructure comprising a trusted device and a server is provided. The method includes the steps: receiving the user identifier as an input to the trusted device; obtaining a hash value of the user identifier; the trusted device obtaining biometric data comprising a facial image of the user; generating a public key and a privacy preserving data structure using the biometric data, encrypting the user identifier using the public key, and storing the encrypted user identifier as metadata in the privacy preserving data structure, wherein a private key for decrypting the encrypted user identifier can be generated from the privacy preserving data structure using subsequently acquired biometric data comprising the facial image of the user; generating a device token corresponding to the trusted device and obtaining a hash value of the device token, the server storing the privacy preserving data structure uniquely indexed by the hash value of the device token while using the hash value of the user identifier as a primary key, and the trusted device storing the device token.

Systems and methods for validating and securing transactions are provided. A registration process can include receiving, via a short-range communication antenna of a mobile device, encrypted data from a contactless card, successfully decrypting the encrypted data to authenticate the contactless card, receiving, via the mobile device, first biometric data, and storing the first biometric data in a biometric profile of a customer account associated with the contactless card. An authorization process can include transmitting a solicitation message to the mobile device responsive to receiving a request to authorize a digital transaction in connection with the customer account, receiving, via the mobile device, second biometric data responsive to the solicitation message, comparing the second biometric data with the biometric profile, authorizing the digital transaction when the second biometric data matches the biometric profile, and denying the digital transaction when the second biometric data fails to match the biometric profile.

The invention provides an automobile cabin end side model multi-modal perception enhancement method, which comprises the following steps: S1) deploying an RGB camera in a cabin, and collecting facial biological characteristic data, hand interaction behavior data and cabin overall environment data of a driver; s2) adjusting image illumination and contrast by adopting an algorithm, dynamically focusing a key area through a target detection frame to process a shielding problem, and eliminating static redundant information; s3) constructing a neural network, extracting facial biological features and the like in parallel, and outputting low-dimensional feature vectors; s4) time sequence association is established, key area feature weights are enhanced through a space attention mechanism, and a logic relationship among different features is explicitly modeled; s5) aggregating the weighted feature maps by using feature attention pooling, and retaining a core feature channel in combination with a channel pruning technology to realize model compression; s6) dynamically adjusting the calculation priority and weight distribution of each feature extraction branch; and S7) the end side uploads the sample to the cloud side, and the cloud side generates an update package and pushes the update package to the end side to complete model iteration.

A system for authenticating a user includes a memory device, and a processor. The processor is configured to receive a first biometric sample associated with a user from a biometric measurement device, and receive, substantially contemporaneously with receiving the first biometric sample, an image of a user credential, where the image includes credential data, such as any of a variety of personally identifiable information. The processor may also be configured to compare the received first biometric sample to at least one of: i) a second biometric sample included in the credential data, or ii) a third biometric sample stored by an authentication database in association with the user. Likewise, in at least some embodiments, the processor may determine whether to authenticate the user, such as based upon the comparison.

An authentication system for verifying creation of digital content includes a machine learning classifier configured to analyze data points related to a content creation process, a programmatic rules-based analysis component configured to apply predefined criteria to the data points, and a human-viewable replay component configured to provide a visual representation of the content creation process. The authentication system is configured to determine whether the digital content was created by a human or generated by artificial intelligence (AI) based on outputs from the machine learning classifier, the programmatic rules-based analysis component, and the human-viewable replay component. The data points may include keystroke dynamics, syntax and style analysis, error patterns and corrections, content revision history, behavioral data, content creation timeline, gestures and touch interactions, brushstrokes and drawing patterns, voice and audio analysis, physical interaction with devices, eye tracking and gaze patterns, and biometric data.

A method and system are disclosed for creating a graphic element representing encoded biometric data that represents the facial biometrics of two or more individuals. The method includes capturing facial images of each person, generating non-reversible face-derived feature vector data, and embedding this data into a graphic on the item. To validate that the graphic is derived from the people presenting the graphic, the graphic is processed to extract corresponding feature vector data, which is compared to the data derived from newly collected facial images of the presenting people. Validation indicators are based on threshold comparisons. The system supports verification using photographs on the item and enables secure association through trusted entities and cryptographic signatures. The graphic may encode alpha-numeric strings representing biometric and document data. The graphic may be applied to any document or item, including driver's licenses, passports, titles, ballots, and financial instruments.

The invention relates to the field of artificial intelligence and digital medical treatment, discloses a multi-mode intelligent inquiry method and device, computer equipment and a storage medium, and can be applied to inquiry processing of families, drugstores and medical institutions. The method comprises the following steps: receiving biological characteristic data sent by a user terminal to verify a user identity, and obtaining a historical medical record of a user according to the user identity; receiving chief complaint symptoms and multi-modal physiological data, uploaded by the user terminal, of the user; fusing the chief complaint symptoms, the multi-modal physiological data and historical medical records, and constructing a dynamic knowledge graph; and generating a medication suggestion based on the dynamic knowledge graph and feeding back the medication suggestion to the user terminal. According to the method, the chief complaint symptom and the multi-modal physiological data are collected through the user terminal, intelligent monitoring of the user symptom is achieved, the dynamic knowledge graph is constructed by fusing the chief complaint symptom, the multi-modal physiological data and the historical medical records, efficient diagnosis decision is achieved, and the progress of medical digitization is promoted.

The invention provides a vehicle self-adaptive control method and device, relates to the technical field of vehicle control, and automatically triggers a vehicle to enter a meditation control mode by monitoring that at least one of target vehicle operation data and target user biological characteristic data meets a meditation triggering condition, initiatively intervenes in an abnormal early stage, and avoids risk accumulation. Moreover, non-intrusive guidance is output by driving a preset execution mechanism of the vehicle, and driving operation and meditation guidance are synchronously fused, so that the user gradually transits from a bad driving state to a relaxed positive state on the premise of not dispersing the attention of a road. The physical and mental pressure can be effectively relieved, the driving safety can be improved, and the problem of conflict between meditation intervention and driving is solved fundamentally.

The system includes a processor that works with a full-body fitting garment equipped with internal sensors and low-frequency pads. It collects biometric data, connects wirelessly to an external device via a control unit, and uses an AI module to visualize the user's relaxation state. Based on this, it generates instructions to optimize relaxation and controls the pads accordingly.

A method for generating reference biometric data based on a bending of a flexible device is described. In one aspect, a method includes forming training data includes bending estimates of a flexible device worn by a first user, training a model based on the training data, and generating reference biometric data for the first user based on the model.

The present disclosure is related to blockchain technologies, tokenization and non-fungible token (NFT) technologies, identity verification, account verification, information security (InfoSec), and fraud prevention technologies, and in particular, to technologies for creating NFT identities (IDs) for individuals and / or organizations. An NFT ID service interacts with users to obtain ID information such as ID documents, biographical data, biometric data, and / or any other suitable data. The NFT ID service includes an NFT ID engine that generates an NFT-based form of digitized and / or tokenized ID, using blockchain technology, smart contracts, distributed ledgers, digital wallets, and the ID information. Other embodiments may be described and / or claimed.

A system for authenticating a sender of a response to an authentication request includes an authentication server, an identity server configured to receive biometric data of a user, a central ID system configured to create or receive a username and / or password, and a first user device associated with a first user. The first user device is configured to create a first user ID that includes at least a first username and a first biometric data. When an authentication request is sent to a user device by the authentication server the user device responds with a user ID. The authentication server then queries at least one or both of the central ID system and the identity server to certify the accuracy of the user ID to assure it matches the first user ID before (1) accepting the response, or (2) permitting the first user to access confidential information. The systems and methods may also include blockchain authentication or tuple space authentication.

A system comprises a video capture module to acquire a video, a preprocessing module to enhance video quality and isolate regions of interest within the video, and a biometric data extraction module using remote photoplethysmography to extract heartbeat and SpO2 levels from the video. A machine learning module analyzes the extracted biometric data for liveness and deepfake detection, a verification module to compare the analyzed data against known biometric signatures, and a user interface to display analysis results and alerts.

A driver support system includes: an acquisition unit that acquires biometric data of a driver of a moving object; an evaluation unit that evaluates a health condition of the driver; and an interactive response unit that executes an interaction operation for interactive response with the driver using an HMI device mounted on the moving object, the evaluation unit being configured to; when estimating based on the biometric data for the driver that the health condition of the driver is poor, instruct the interactive response unit to execute the interaction operation, thereby acquiring a response input, which is a response of the driver to a response facilitating output that facilitates the driver to respond in the interaction operation; and determine the health condition of the driver based on a degree of suitability of the response input to the response facilitating output.

An apparatus for biometric access control is disclosed. The apparatus includes an outer body configured to house a plurality of internal components and a power source disposed within the outer body, wherein the power source is configured to provide power. Additionally, the apparatus includes a biometric sensor connected to the power source, wherein the biometric sensor is configured to receive biometric data associated with a user and a processing circuit communicatively connected to the biometric sensor. The processing circuit is configured to send identification data to an external device, receive an external response generated by the external device based on the identification data, and activate the biometric sensor based on the external response received from the external device.

Nutritional Cognitive Behavioral Therapy (Nutritional-CBT) is provided for the treatment of patients with type 2 diabetes and other cardiometabolic diseases, addressing common maladaptive thinking and beliefs pertaining to diet and lifestyle in a digitally-delivered therapy personalized to the individual patient using artificial intelligence (AI) / machine learning (ML) driven feed-back loops. Systems, methods, and computer-readable media described herein can include providing, by one or more processors, a digital therapeutic application including one or more lessons or activities. The one or more processors can collect at least one response or biometric data from the user. The one or more processors can generate, using a machine-learning model, one or more goals for the user to achieve or a progress overview.

A method for generating reference biometric data based on a bending of a flexible device is described. In one aspect, a method includes forming training data includes bending estimates of a flexible device worn by a first user, training a model based on the training data, and generating reference biometric data for the first user based on the model.

An apparatus for biometric access control is disclosed. The apparatus includes an outer body configured to house a plurality of internal components and a power source disposed within the outer body, wherein the power source is configured to provide power. Additionally, the apparatus includes a biometric sensor connected to the power source, wherein the biometric sensor is configured to receive biometric data associated with a user and a processing circuit communicatively connected to the biometric sensor. The processing circuit is configured to send identification data to an external device, receive an external response generated by the external device based on the identification data, and activate the biometric sensor based on the external response received from the external device.

An example operation may include one or more of receiving application data via at least one data prompt on an application form on a computing device, receiving device data from the computing device, executing a trained artificial intelligence (AI) model to predict a data validity risk level based on the application data and the device data, determining at least one identity check to be performed based on the predicted data validity risk level, determining at least one additional data prompt needed to execute the at least one identity check, analyzing the application data being received, augmenting the application form on the computing device with the at least one additional data prompt based on the analyzed application data, wherein the at least one additional data prompt requests biometric data, wherein a type of biometric data is based on an amount the predicted data validity risk level is above a threshold, receiving additional application data based on the at least one additional data prompt on the computing device, and executing the at least one identity check based on the received additional application data.

Systems and techniques may be used for multiple biometric data authentication. An example technique may include receiving first biometric data and second biometric data, optionally combining the first biometric data and the second biometric data into combined biometric data, and comparing the first and second or the combined biometric data to stored biometric reference data associated with an account of a user to generate a similarity score. The example technique may include determining whether the similarity score exceeds a threshold value, and in response to determining that the similarity score exceeds the threshold value, outputting an indication.

A system for authenticating a sender of a response to an authentication request includes an authentication server, an identity server configured to receive biometric data of a user, a central ID system configured to create or receive a username and / or password, and a first user device associated with a first user. The first user device is configured to create a first user ID that includes at least a first username and a first biometric data. When an authentication request is sent to a user device by the authentication server the user device responds with a user ID. The authentication server then queries at least one or both of the central ID system and the identity server to certify the accuracy of the user ID to assure it matches the first user ID before (1) accepting the response, or (2) permitting the first user to access confidential information. The systems and methods may also include blockchain authentication or tuple space authentication.

Systems and processors associated with an electronic keyboard are described. An example system includes an electronic keyboard with a threshold number of keys extending across a first width; and a display positioned above the electronic keyboard, the display extending at least as wide as the first width. The display provides real-time visual prompts aligned with each key, including the partially covered edge keys, and hosts an Al-driven user interface. A camera may capture a player's posture, hand position, gaze, and facial expressions. Transformer-based models may process inputs to generate adaptive feedback, emotion-aware coaching, and / or gamified scoring. Haptic key actuators, synchronized LEDs, and audio cues reinforce the feedback, while on-device encrypted inference and differential-privacy may filter and secure all biometric data.