16 results about "Attentional control" patented technology

The invention relates to the technical field of intelligent health training, and discloses a personalized training system and method based on inspiration starting and attention turning-back prompt, and the system comprises four core modules: a scheme configuration and calibration module, a respiration data collection module, a core data processing module, and a man-machine interaction and feedback module. Inspiration starting and attention turn-back prompt are taken as double cores, personalized respiration data, respiration visualization and scene parameter adaptation functions are linked, four scene training schemes of pre-sleep relaxation and sleep aiding, meditation respiration calibration training, meditation immersion meditation and concentration training are designed, and low-burden and personalized meditation training meeting different time periods and different requirements is achieved. The technical problems of guidance forcing, synchronous waiting anxiety, lack of state monitoring, single interaction, insufficient scene adaptability and the like of the traditional training equipment for the positive feeling are solved.

The invention discloses an electroencephalogram head ring interaction control method and device based on concentration level, and the method comprises the steps: collecting multi-band electroencephalogram signals and user interaction parameters, carrying out spectrum decoupling analysis to recognize a concentration feature baseline, exporting an attention stability coefficient, and building a cognitive state mapping relation; tracking a high-response frequency band core to implement frequency band fusion analysis to form a control channel, and collecting concentration fluctuation data to construct an interaction control network; executing multi-task response analysis to identify an intention switching point, extracting cognitive load parameters to divide a low-load area and a high-load area, and extracting a recovery rate to construct an attention toughness index in an identification conversion process; determining an optimal trigger position in a low-load area according to an attention toughness index, constructing a brain wave feature chain, aligning the brain wave feature chain with an attention stability coefficient, determining a low-interference response window, and setting a self-adaptive threshold group; and the coupling identification false triggering area extracts redundant brain wave components to execute false triggering suppression to generate an interaction control instruction, so that accurate matching between teaching intervention and the cognitive state of the student is realized.

The invention discloses an online learning concentration maintenance system and method based on multi-modal data perception, and particularly relates to the technical field of concentration perception, comprising personalized baseline establishment, baseline dynamic update, multi-source data acquisition, an attention fusion network, attention loss early warning, concentration attenuation trend evaluation and concentration intervention. According to the method, the personalized initial cognitive base line of the learner is established, the base line is dynamically updated, it is ensured that the base line is always matched with the actual state, the first interaction response data is collected with the synchronous timestamp, concentration evaluation features are output after deep fusion, the deviation degree with the base line is calculated, and the first early warning target is screened out. According to the method, the concentration degree at the current moment is calculated, and the concentration degree attenuation rate is calculated through the concentration degrees at different time points, so that an intervention mechanism is triggered, the abnormal concentration state relative to the normal state of the user is effectively recognized, screening of the first early warning target is more accurate and more personalized, and the allocation strategy of computing resources is optimized.

The invention belongs to the technical field of concentration intervention, and particularly relates to a cognitive load-based concentration adaptive intervention method and system, and the method comprises the following steps: S1, obtaining eye movement tracking data and heart rate signal data of a user in a preset time window; s2, extracting a pupil diameter time sequence signal and a heart rate variability time sequence signal from the data, and performing complementary set empirical mode decomposition and phase locking value calculation on the two signals to obtain a pupil-heart rate phase coupling coefficient representing cognitive load; based on the eye movement tracking data, the scanning entropy, the scanning path backtracking times and the pupil diameter microscopic fluctuation standard deviation are calculated; the intervention measure, the intensity and the guiding direction generated by the method directly correspond to the concentration deviation vector, the user attention regression is guided in a mild and non-intrusive mode, and accurate closed-loop correction of the concentration is realized.

The invention discloses a personalized training recommendation method for concentration dynamic evaluation fused with multi-modal data, relates to the technical field of cognitive training, and is characterized in that multi-modal data acquisition is performed in advance for acquiring multi-dimensional data reflecting the concentration state of a user, the multi-modal data at least comprises behavior data, physiological data and environmental subjective data; based on the multi-modal data, a static basic evaluation model and a dynamic real-time evaluation model are constructed, the static basic evaluation outputs a basic score based on the initial multi-modal data, and the dynamic real-time evaluation calculates a real-time concentration score with 30 seconds as a window and obtains an adjustment result. According to the method, behavior performance, physiological features and environment and subjective feedback are creatively integrated, a double-layer model of static basic evaluation and dynamic real-time evaluation is formed, the limitation of one-time evaluation of a traditional method for life is broken through, it is ensured that the evaluation result is always synchronous with the real state of the user, and an accurate decision basis is provided for subsequent training recommendation.

The present application belongs to the technical field of training teaching aid, and particularly relates to a cognitive impairment operation simulation teaching aid. The cognitive impairment operation simulation teaching aid comprises a training box, a memory test area and a concentration test area separated by a main partition plate; a memory training assembly arranged in the memory test area for memory training; and a concentration training assembly arranged in the memory test area for concentration training. The present application integrates memory training, concentration training and execution training into one through a set of coherent operation processes. While performing memory matching and attention selection, the patient must plan steps and manage time to run faster than the sandglass. This design simulates the complex cognitive requirements in the real world and aims to improve the level of comprehensive use of cognitive ability of the patient in daily life.

The application provides a concentration training method and device based on visual tracking, which comprises the following steps: collecting real-time eye movement data of a user, including a gaze point coordinate and an eye movement speed, and initializing a target trajectory of a training task; calculating a concentration deviation between a current gaze point and the target trajectory, dynamically adjusting the target trajectory through a nonlinear mapping based on the deviation, and generating a dynamic trajectory; based on the concentration deviation and its change trend, combining the geometric features of the trajectory, constructing a distraction score model with multi-feature fusion, and detecting and marking a distraction event; when the distraction event is detected, immediately performing adaptive visual correction stimulation at the event position to guide the user to return to the task; after the training period ends, dynamically adjusting the task difficulty coefficient of the next period according to the frequency and average deviation of the distraction event in the current period.

This application relates to a method and system for attention training that combines EEG and behavioral data, belonging to the field of brain-computer interface data processing technology. The method simultaneously collects EEG and behavioral data during attention training tasks, divides continuous EEG time windows based on a unified time reference, and maps behavioral data to corresponding windows; preprocesses the EEG data and calculates a reliability index, extracting attention features to obtain candidate attention values; extracts behavioral attention features to generate behavioral representation values, and performs consistency verification based on the deviation between the two; combines the reliability index and verification results to perform gating correction on the candidate attention values, obtaining fused attention values ​​and dividing attention state segments; adaptively adjusts the training load according to the type and duration of attention state segments; after training, generates evaluation results based on the distribution of attention state segments and changes in behavioral data, determining the initial configuration for the next cycle. This application can improve the stability of attention state recognition in children's scenarios.

The invention relates to the technical field of intelligent education auxiliary tools, and discloses a picture book reading attention improving method and system based on multi-sensor fusion, and the method comprises the following steps: S1, obtaining eye movement data, sitting posture data and physiological monitoring data of a child, and building a personalized concentration evaluation model in combination with age information, and outputting a personal feature vector containing offset, the offset representing the deviation of the individual concentration feature relative to the reference and being generated by fusing indexes of the calibration task, and establishing an initial decision rule base based on the feature vector. Eye movement, sitting posture and physiological data are collected through multiple sensors, offset representing individual deviation is generated in combination with a calibration task, personal feature vectors are constructed, real-time concentration is calculated by fusing age model reference scores and dynamic attenuation weights, and the accuracy and pertinence of attention state monitoring are remarkably improved.

The invention relates to the technical field of child promotion concentration training, in particular to an evaluation auxiliary seat, an evaluation system and an evaluation method for promotion concentration training. The evaluation auxiliary seat for improving the focused training comprises a seat body, the seat body comprises a cushion, and the cushion comprises a supporting seat; a plurality of pressure sensors and a supporting plate are arranged on the upper portion of the supporting base in a surrounding mode, and the supporting plate is jointly supported by the pressure sensors. A plurality of pressure sensors are dispersedly arranged on the supporting plate; a user sits on the cushion, the sitting data of the user is collected through the multiple pressure sensors and the pressure sensor, and the sitting data of the user is used for judging the sitting posture of the user. The method has the advantage that the problem that the change process of concentration is difficult to quantify and analyze in the process of promoting concentration training for children at present is solved.

The invention belongs to the technical field of training teaching aids, and particularly relates to a cognitive disorder operation simulation teaching aid. Comprising a training box which is divided into a memory testing area and a concentration testing area through a main partition plate; the memory training assembly is arranged in the memory testing area and is used for training memory; and the concentration training assembly is arranged in the memory testing area and is used for training concentration. According to the invention, through a set of coherent operation processes, memory training, concentration training and execution training are organically integrated. When a patient carries out memory matching and attention selection, the patient must plan steps and manage time to win and win the hourglass. The design simulates the complex cognitive demand of the real world, and aims to improve the level of comprehensive cognitive ability application of the patient in daily life.

The invention relates to the field of rehabilitation training, in particular to a cognitive impairment rehabilitation training prompting instrument. The invention provides a cognitive impairment rehabilitation training prompting instrument which can fully and effectively enhance the memory of a patient and improve the cognition of the patient. A cognitive impairment rehabilitation training prompting instrument comprises a base, a shell and the like. A shell is placed on the base. During training, a patient closes eyes, when a nurse shouts out numbers, the patient puts hands into the shell, when the number shouts out by the nurse is counted, one spherical handle is pressed down, so that one character block moves downwards, and the nurse can see whether the number on the character block is correct or not through the groove in the shell; a patient carefully listens to digits shouted by nursing personnel to improve concentration, and then finds the corresponding spherical handle according to the shouted digits, so that the thinking power of the patient is exercised, and the effects of enhancing memory and improving whole cognition are fully and effectively achieved.

The invention provides a teenager concentration training system and method, and the method comprises the steps: carrying out the gaze cluster clustering of eye movement data when a target teenager is subjected to a visual search task, and obtaining a search mode feature; determining a concentration attenuation trend based on the ability portraits of the target teenagers for concentration training and the search mode features; performing similarity matching on the action trajectory of the target teenager in the concentration training process and a standard action trajectory of concentration training to obtain a behavior cooperation coefficient; and generating an adaptive regulation factor of concentration training based on the concentration attenuation trend and the behavior cooperation coefficient, and adjusting the density and moving speed of interference elements in the visual search task in the next concentration training stage according to the adaptive regulation factor. By adopting the scheme of the invention, dynamic regulation and control of training task parameters can be realized by constructing a collaborative perception mechanism of eye movement-limb multi-mode man-machine interaction data so as to improve the training efficiency of teenager concentration.

The application provides a continuous concentration evaluation system and method based on multi-dimensional data, and belongs to the technical field of attention evaluation. The system comprises a multi-dimensional data acquisition module for acquiring multi-dimensional test data; a curve construction module for constructing a baseline and generating an individual curve with the same characteristics as the baseline by using a sliding window technology; an analysis module for performing abnormality judgment when the individual curve is generated; and a control module for extracting the decay eigenvalue of the individual curve by using a symmetric rotation and other convolution technology during the early warning observation period, and starting an evaluation termination mechanism when the decay eigenvalue still shows abnormality at the end of the early warning observation period. Through multi-modal data fusion and individual baseline construction, the application realizes high-precision dynamic identification of the attention decay process, and outputs the continuous concentration time length as an evaluation index based on the evaluation start and end time, thereby significantly improving the accuracy and individual adaptability of the concentration evaluation.

The present application belongs to the technical field of concentration intervention, and particularly relates to a concentration adaptive intervention method and system based on cognitive load, which comprises the following steps: S1, acquiring eye movement tracking data and heart rate signal data of a user within a preset time window; S2, extracting a pupil diameter time sequence signal and a heart rate variability time sequence signal from the data, and obtaining a pupil-heart rate phase coupling coefficient representing cognitive load by performing complementary ensemble empirical mode decomposition and phase lock value calculation on the two signals; and based on the eye movement tracking data, calculating saccadic entropy, saccadic path backtracking frequency and pupil diameter microfluctuation standard deviation. The intervention measures generated by the present application directly correspond to the vector of concentration deviation in terms of strength and guidance direction, and guide the user's attention to return in a mild and non-invasive manner, thereby realizing precise closed-loop correction of concentration.