8 results about "Autism child" patented technology

The application relates to a medical engineering technology, in particular to a control method and system of a diagnosis and treatment robot for autistic children. The control method comprises the following steps: analyzing a human face video by using a deep learning model; generating a next-step intervention action recommendation list by using an LSTM state prediction model and a CPT action decision model; selecting or modifying one of the recommendation items and executing; retraining and updating the LSTM state prediction model and the CPT action decision model by using new interaction data. The control system comprises an execution module, a perception module, a memory module, an evolution module and a decision module. By introducing the quantification calculation of the concentration of the children and the valence and arousal of the facial expression, and by using the LSTM to predict the future state, the strategy can be adjusted in advance when it is predicted that the children will lose interest, so that the children's boredom or escape behavior is not easily caused, and meanwhile, the model is retrained and updated, so that the self-learning and adaptation capability is high, and the auxiliary diagnosis and treatment capability is relatively high.

The application discloses an autism child social interaction behavior video image analysis method and system, belongs to the technical field of computer vision and medical image analysis, and comprises the following steps: a video acquisition step, wherein video images of a child and an assessor performing a structured social interaction task are acquired through a multi-angle camera; a human body posture estimation step, wherein two-person skeleton key point detection is performed and posture parameter sequences are calculated; a social signal detection step, wherein key social behavior events such as eye contact, social smile, directional gesture and body orientation response are identified; an interaction synchronism analysis step, wherein the time coupling degree of posture changes of both parties is calculated through cross-correlation analysis; and an evaluation report generation step, wherein a social interaction ability evaluation report is generated in the form of a radar chart by comprehensively considering multi-dimensional features. The application realizes objective quantitative evaluation of the social interaction ability of an autism child and improves the consistency and repeatability of evaluation.

This invention discloses a method for screening autism children based on eye movement detection using ordinary video. The method comprises a video acquisition unit, a preprocessing unit, an eye movement estimation unit, a scene analysis unit, a feature quantization unit, a screening inference unit, and a display unit. It uses an ordinary camera to capture facial video of children, integrates head posture compensation to achieve label-free eye movement tracking, automatically segments dynamic social regions and extracts autism-specific eye movement features, completes risk screening through a lightweight model, and outputs a visual report. This invention requires no professional eye tracker, no head fixation, is suitable for children with low cooperation, and is fully automated. It has the advantages of low cost, strong robustness, good interpretability, and ease of implementation at the grassroots level, making it suitable for large-scale early screening of autism children.

The application belongs to the technical field of autism children rehabilitation evaluation, and discloses an autism children rehabilitation evaluation method, system and device based on an MREP mode, which converts the performance of children on target evaluation projects into quantitative feature data through structured behavior quantitative coding, calculates the abnormality of children in four dimensions of medical treatment, rehabilitation, education and family based on the data, screens out a primary intervention target set in combination with development lag judgment, automatically matches a structured intervention scheme for each target and sorts and executes the structured intervention scheme by querying a preset evidence-based intervention mapping matrix, collects process data of institutions and families within an intervention period, and calculates a progress index of each target according to the process data, and obtains a comprehensive evaluation value by weighting the average mastery degree of each dimension target and the overall target achievement rate. The application realizes the full-process data of collection, intervention and effect evaluation, and improves the accuracy, scientificity and efficiency of rehabilitation services.

The application is suitable for the technical field of behavior recognition, and provides an autism child stereotyped behavior recognition classification system and method based on RMG-transformer, which comprises the following steps: video data acquisition and preprocessing; repeated action segment detection; super image construction; feature extraction and behavior classification; and recognition result output. The repeated action detection submodule and the super image submodule are innovatively introduced in the original Transformer network architecture, and the loss function is further optimized, so that the efficiency can be improved according to the characteristics of the stereotyped behavior repetition, and the time sequence characteristics are enhanced, and the recognition ability of continuous actions is improved.

This invention discloses a method for guiding picture book reading for children with autism based on emotional segmentation and visual silent cues. The method includes: extracting and fusing emotional features from the picture book text and illustrations to construct an emotional arc and segmentation boundaries; collecting children's responses to establish a perceptual sensitivity vector; calculating the cumulative load value of subsequent pages based on an emotional aftershock model when turning pages, generating a risk timeline; collecting emotional observation values ​​in real time, using Kalman filtering to track the baseline and calculate the deviation value; combining the deviation value and the risk timeline to determine trigger rules, generating cue parameters based on the intervention urgency, and executing visual silent cues; after the session, bidirectionally correcting the emotional labeling values, and using the least squares method to fit the aftershock sequence and update the individual attenuation coefficient. This invention achieves preventative intervention through the cumulative effect of emotion, and the bidirectional self-correction closed loop improves accuracy, making it suitable for assistive therapy through picture book reading for children with autism.