16 results about "Attention Concentration" patented technology

The invention belongs to the technical field of video management, and particularly relates to a video management method based on artificial intelligence. The method comprises the following steps: firstly, extracting an interest value of a user in a video watching process through facial recognition and expression analysis, and judging an attention concentration time frame; and then text features and scene features of the time frame and the advertisement video key frame are extracted, semantic alignment and matching scoring are performed on the video and the advertisement by using a cross-modal matching model, and the advertisement with high matching degree is screened and inserted into the video. The system further collects interaction behavior data generated after the user watches the advertisement, calculates the advertisement adhesion score, dynamically adjusts the advertisement putting strategy, and achieves the continuous optimization of the advertisement effect. The method improves the correlation between the advertisement and the video content and the user experience, and has the advantages of high precision, high adaptability and the like.

A heart rate measurement and mental state detection system and a heart rate measurement and mental state detection method for measuring heart interbeat interval and detecting a direction of attention of an individual engaged in an activity are disclosed. The heart rate measurement and mental state detection and method are configured to instantaneously detect and measure focused attention of an individual during a pre-action phase before the individual performs an action involved in an activity while the individual engages in the activity.

The invention provides a touch head structure of a palm device for improving concentration and a concentration reminder, the touch head structure is used for being arranged on a holding body, the touch head structure comprises a rotating part, the rotating part is provided with a mounting part, and the mounting part is used for being connected with the holding body and is driven by the holding body to rotate around the mounting part; the first elastic piece is arranged at the first end of the rotating piece; the first contact pressure head is connected with the first elastic piece and is far away from the rotating piece through the pushing force of the first elastic piece; the second contact pressure head is arranged at the second end of the rotating piece; and through the rotation of the rotating piece, the first touch pressure head and the second touch pressure head are matched with each other and respectively abut against the palm of a user to move. The problems that a user cannot keep attention concentrated for a long time and is prone to distraction or sleepiness are solved.

The invention discloses an attention state detection device, and relates to the technical field of computer vision. In the device, eye movement characteristics are acquired through a first acquisition module, then behavior characteristics are determined based on the eye movement characteristics in a first determination module, and finally, the attention state is determined based on a pre-established attention stage, a pre-established mapping relation between the behavior characteristics and a threshold value and the current behavior characteristics in a second determination module. In the attention detection device, the attention is divided into a plurality of stages in advance, such as a visual search characterization stage, a sight orientation characterization stage, an attention maintenance characterization stage and an attention concentration characterization stage, and a mapping relationship among the attention stages, behavior characteristics and threshold values is pre-established, so that the attention detection accuracy is improved. According to the invention, the existing attention stage and the missing attention stage can be determined based on the mapping relation and the current behavior characteristics, so that the user can know the specific stage where the attention is missing, and the accurate judgment of the attention state is realized.

The invention discloses a mental improvement algorithm based on human-computer interaction, and the algorithm comprises the following steps: S1, collecting the behavior data, cognitive ability indexes and learning preferences of a user through a human-computer interaction interface, and constructing an initial cognitive feature vector containing the attention concentration degree and cognitive style classification; and S2, based on a cognitive challenge module, dynamically generating a multi-dimensional interaction task according to the current cognitive level of the user. According to the method, fusion of cross-domain task complexity and a neuroscience incentive mechanism is dynamically adjusted through the fuzzy logic controller, and accurate balance between cognitive challenge and individual adaptive learning is achieved. Compared with a traditional mental training algorithm, a semantic network analysis technology is introduced into cross-domain knowledge association task generation, and the problems of task staticization, excitation simplification and path linearization in a traditional algorithm are effectively solved in combination with a three-dimensional cognitive map constructed by a map attention network and a deep reinforcement learning optimization strategy.

The invention relates to the technical field of medical robots, in particular to a method, a system and equipment for autonomously collecting questionnaire information of a robot with a body in a medical scene and a storage medium. Receiving the questionnaire collection task, planning a navigation path and controlling the robot to move to the position of the target patient; collecting state information of the patient; calculating an attention concentration degree value of the patient based on the eye features and the trunk posture features, and judging an emotional state category of the patient based on the facial muscle motion features; when the attention concentration degree numerical value and the emotional state category meet the interaction condition, playing a voice inquiry of the current question; receiving a voice response of the patient, converting the voice response into a response text, judging whether the response text is consistent with a preset answer format of the question, if so, storing the response text and switching to the next question, and if not, playing the guide voice and replaying the current question; after all questions are collected, a structured questionnaire record is generated, and the robot with the body is controlled to return to the charging station.

The present disclosure relates to the technical field of computers, in particular, to a word-based video recommendation method and device, medium and electronic equipment. The method comprises: determining a plurality of words to be learned and a word order of the words to be learned according to the words in a word book; determining a target definition of the words to be learned, and determining a learning video corresponding to each word to be learned according to the target definition; and displaying the learning video corresponding to each word to be learned according to the word order. In this way, for each word to be learned, the user can focus on understanding and learning the application of the word to be learned under the target definition, thereby improving the mastery and application of the word to be learned. In addition, through the display of the learning video, the real usage scenario of the word to be learned can be restored, effectively improving the user's attention concentration in learning the word, improving the user's learning pleasure, reducing the boredom of word learning, and further accelerating the speed of mastering the word.

The present invention aims to create the ideal conditions for a user to consume and interact with digital content in a simple, effective and distraction-free manner. In order to achieve this aim, it provides the possibility of accessing the content by various means, with particular emphasis on physical media such as content discs or release discs. After accessing the content, the user experiences simplified navigation, free from distractions or interruptions. In addition to providing access to the content, the device has mechanisms to measure the user's level of attention and focus, as well as their stress and emotional state, while they are using the device. Some of these mechanisms are embedded and operate by means of an infrared camera mounted on the main device. Other mechanisms can be included by means of connecting peripherals such as an EEG, a heart rate sensor and a galvanic skin response sensor. The data resulting from these measurements are combined and used to provide feedback to the user and to personalise their content consumption experience. Finally, the user's focus and sense of immersion can be enhanced by means of using a pair of virtual reality glasses as a peripheral. These glasses may or may not have an integrated EEG and when connected to the device, provide new possibilities for viewing and interacting with the content.

The invention discloses an advertising effect analysis method and system based on artificial intelligence, and relates to the technical field of commercial advertising prediction, the advertising effect analysis method based on artificial intelligence can significantly improve the accuracy and effectiveness of advertisement putting, and through multi-modal biological feature collection, the advertising effect is improved. Data of brain waves and eye movement tracks when consumers watch advertisements are obtained in real time, the nerve excitement degree, the attention concentration degree and the emotional response of the consumers are deeply known, a nerve behavior decoding engine constructs a three-layer cognitive mapping model based on the data, the real-time transformation probability of the consumers is accurately predicted, and the conversion efficiency of the consumers is improved. The dynamic advertisement gene pool specifically adjusts visual, auditory and narrative elements of the advertisement according to the prediction result, personalized customization of the advertisement content is achieved, the accurate advertisement putting mode can better meet the requirements and interests of consumers, the matching degree of the advertisement and the consumers is improved, and therefore the conversion rate of the advertisement is effectively improved.

The invention relates to an audio-visual language audience response evaluation system and method based on multi-view synchronous perception and data fusion. The system comprises an adjustable viewing angle watching platform, an audio-visual content playing module, a synchronous perception acquisition module, a subjective feedback acquisition module, a multi-modal data fusion analysis module and an evaluation result output module, eye movement data, physiological signals and behavior responses of audiences can be synchronously acquired in real time at different watching angles, and subjective feedback information is combined, so that the audiences can be evaluated in real time. And the perception intensity, the attention concentration degree, the cognitive load and the emotion titer of the audience are comprehensively evaluated. The system can be widely applied to the fields of audio-visual language content optimization, immersive medium design and audience experience research, and has the advantages of being flexible in view angle switching, high in data fusion degree, high in analysis precision and the like.

The invention relates to the technical field of intelligent analysis, regulation and control of resources, in particular to an intelligent analysis, regulation and control system for anesthesiology department operating room resources. Eye movement, physiology and operation behaviors of an operator are collected through a multimode parameter collection device group to obtain eye movement signal parameters, pulse wave signal parameters and operation behavior signal parameters, and then the attention concentration degree, the working memory load and the pressure index are analyzed and output through a multi-task deep learning model. Accurate recognition of the cognitive state of the operator is realized, and data support is provided for subsequent cognitive scene division; according to the method, the multi-dimensional cognitive state vector is analyzed through the cognitive scene division mechanism to obtain the corresponding cognitive decision scene, the cognitive decision scene is analyzed through the rendering control mechanism to output the rendering control strategy, invalid information interference and operation interaction cost are reduced, cognitive burden is reduced, decision efficiency and accuracy are improved, and user experience is improved. And the safety and the high efficiency of operating room resource regulation and control are ensured.

The present application relates to the field of intelligent lighting, and an embodiment of the present application provides a self-study room healthy lighting method based on dynamic adjustment of illumination parameters, which comprises the following steps: acquiring reservation information and human body sensing information in a self-study room; generating a self-study time planning table according to reservation duration information and attention concentration time range; acquiring learning behavior information of a learner at a preset time before the end of a self-study time period; acquiring an attention level according to the learning behavior information and the human body sensing information; determining an illumination parameter change rate according to the attention level and a difference between light environment regulation parameters and rest illumination parameters; and controlling a light source to switch from the light environment regulation parameters to preset rest illumination parameters according to the illumination parameter change rate during a rest time period. The present application solves the problem that the light in a self-study room cannot be dynamically switched to a suitable lighting mode and cannot provide a healthy and comfortable lighting light environment for learners.

A system and method relating to a brain-computer interface in which a visual stimulus overlaying one or more objects is provided, at least a portion of the visual stimulus having a characteristic modulation. The brain computer interface measures neural response to objects viewed by a user. The neural response to the visual stimulus is correlated to the modulation, the correlation being stronger when attention is concentrated upon the visual stimulus. The visual stimulus includes a feedback element that varies according to a measure of attention on the or each overlaid object.

The present application belongs to the technical field of video management, and particularly relates to a video management method based on artificial intelligence. The method first extracts the interest value of the user during the process of watching the video through facial recognition and expression analysis, and determines the time frame of attention concentration. Then, the text features and scene features of the time frame and the key frames of the advertisement video are extracted, the cross-modal matching model is used for semantic alignment and matching score of the video and the advertisement, and the advertisements with high matching degree are screened and inserted into the video. The system further collects the interactive behavior data generated after the user watches, calculates the advertisement sticking score, dynamically adjusts the advertisement delivery strategy, and realizes the continuous optimization of the advertisement effect. The method improves the relevance of the advertisement and the video content and the user experience, and has the advantages of high precision and high adaptability.

The invention relates to the technical field of artificial intelligence, education robots and state perception, in particular to an interactive education robot system based on artificial intelligence. The system comprises an acquisition judgment module, an efficiency analysis module and an interaction guide module. The sitting posture state data and the micro-expression feature data of the learner are collected in real time through the collection and judgment module, the learning state of the learner is judged, if the learner is in an attention concentration state, the current learning state is maintained, and if the learner is in an inattention state, the efficiency analysis module dynamically adjusts the difficulty of the current knowledge point according to the matching degree. And the interaction guiding module generates an interaction problem associated with the current knowledge point by using a multi-dimensional data association method, and guides the learner to gradually enter a learning state, so that accurate recognition of an efficient / inefficient learning state is realized, and the matching degree of teaching content and the ability of the learner is effectively improved.

The application belongs to the field of special education assistance and rehabilitation evaluation, and particularly relates to an immersive sensory training and evaluation method for special education needs. A method named "an immersive sensory training and evaluation method for special education needs" is disclosed, aiming to solve the problems of strong subjectivity and coarse data granularity of existing evaluation. The steps include: constructing a virtual scene and defining a standard trajectory; capturing data such as eye movement visual line, head pose and limb end in real time; comparing the actual trajectory with the standard trajectory by using the DTW algorithm, and extracting the offset and lag features; calculating the attention concentration and motion smoothness through visual line collision detection and Jerk value quantification; and finally automatically generating a digital evaluation report containing a space behavior heat map. Through the above scheme, the application realizes the transformation of evaluation from qualitative observation to quantitative analysis, significantly improving the objectivity, accuracy and scientificity of rehabilitation evaluation.