20 results about "Autism" patented technology

This application relates to the field of biomedical technology, and in particular to a method for evaluating the effectiveness of autism intervention and its application. The method includes the following steps: collecting a test sample and a control sample; the test sample is a urine sample from an autism patient, and the control sample is a urine sample from a healthy volunteer; processing the test sample and the control sample separately to obtain NMR samples; testing the NMR samples using an NMR spectrometer to obtain NMR spectra; performing multivariate statistical analysis on the NMR spectra to construct a urinary metabolite model; and using the urinary metabolite model to screen and evaluate autism patients. This application provides a method for evaluating the effectiveness of autism intervention and its application, constructing a urinary metabolite model through NMR metabolomics technology, providing practical evidence for establishing methods for early screening and treatment process evaluation of autism.

This invention provides a method and system for recommending autism interventions based on knowledge graphs and enhanced retrieval, comprising: receiving multimodal data of individuals with autism; performing feature extraction and semantic analysis on the multimodal data to abstract it into structured evidence entities; utilizing multi-source medical knowledge information in the autism domain to perform structured transformation and entity representation, constructing a knowledge graph in the autism domain, introducing a scale alignment mechanism, calculating the semantic similarity of assessment items in different assessment scales, constructing a unified representation space across scales, and incorporating the alignment results as a component of the knowledge graph; using the evidence entities as the starting point for reasoning, performing knowledge retrieval under evidence constraints in the knowledge graph, filtering target strategies that match individual characteristics from candidate intervention strategies through multi-evidence fusion and matching degree calculation, and generating autism intervention recommendation results including intervention goals, implementation methods, and knowledge sources by combining a large language model.

This invention relates to the field of medical information processing and intelligent decision-making technology, and particularly to an autism decision assessment system based on multivariate data and knowledge graphs. The autism decision assessment system based on multivariate data and knowledge graphs includes the following components: a time-locked random calculation module: collecting endogenous and exogenous data, and determining time lock and random variables based on the endogenous and exogenous data; an arousal graph correction module: obtaining the endogenous arousal level based on the time lock and random variables, constructing a knowledge graph based on the endogenous and exogenous data and combining the endogenous arousal level, and correcting the knowledge graph; and a decision assessment output module: performing autism decision assessment based on the corrected knowledge graph. This invention integrates physiological and environmental time-series data, and through mutual information phase-locked detection, randomized causal graph construction, and individualized extreme value modeling, decouples endogenous and exogenous confusion, improving the accuracy and interpretability of autism assessment.

The utility model relates to the field of seat structure, especially to a seat structure for special needs students in school, including chair foot, chair face and chair back, the chair face upside and downside are connected with chair back and chair foot respectively, the chair face is inclined to the chair back, the first included angle of the virtual plane of the extension of the chair face plane side to the chair back and the ground is acute angle, the second included angle of the side of the chair foot close to the chair back and the ground and the first included angle are mutual, through the design of the inclined chair face, the gravity of the student sitting posture can be changed, so that it is inconvenient to get up and leave the seat, reduces the problem behavior frequency, helps the autism student to participate in the learning activity better, through the mutual design of the included angle of the chair face and the ground and the included angle of the chair foot and the ground, the stability of the seat structure is ensured.

The present disclosure relates to the field of biomedicine, and discloses a nutritional composition for intervention or treatment of autism and a preparation method thereof, aiming to solve the problems of safety, compliance and insufficient targeting mechanism of existing intervention programs for social impairment of autism. The composition comprises leucine, isoleucine and valine in a molar ratio of 1:1:1, with a total concentration of 0.753 mg / kg of body weight, in the form of oral liquid, and a pH of 6.87.4. The preparation method comprises weighing the amino acids according to the molar ratio, dissolving them in 0.9% sodium chloride injection, filtering, dispensing and sealing. The present application can safely and effectively improve the social impairment of autism patients and plays a role by up-regulating the expression of MyT1L in the hippocampus.

This invention relates to the field of rehabilitation data communication technology, specifically a method for integrated medical and educational multimodal data acquisition and analysis for autism rehabilitation. The method includes: constructing a set of multimodal data acquisition units; performing integrated autism rehabilitation data detection based on these units to obtain multimodal rehabilitation data; if the multimodal rehabilitation data contains anomaly tags, transmitting the data to the original receiving terminal via an emergency transmission channel to obtain the target receiving terminal; if the multimodal rehabilitation data does not contain anomaly tags, recording it as normal polling data; summarizing the normal polling data to obtain a normal polling dataset; and transmitting the normal polling dataset to the original receiving terminal to obtain the target receiving terminal. This invention can improve the accuracy of rehabilitation status monitoring and reduce the risk of missed reports of abnormal conditions.

A protective shirt designed to prevent puncture and abrasion injuries while maintaining comfort, flexibility, and a professional appearance. The shirt includes a multi-layer fabric construction comprising an outer layer of spacer fabric for cushioning, a middle layer of puncture-resistant material such as para-aramid fibers (e.g., Kevlar®), and an inner layer of soft jersey knit fabric for skin comfort. The shirt features long sleeves with integrated cuffs and thumb openings, a front yoke with a zipper for easy wear, and strategically positioned breathable mesh panels at the underarms and back for temperature regulation. Suitable for medical professionals, educators, mental health providers, and individuals with autism or other conditions that may lead to self-injury, the shirt combines protection with aesthetics and mobility. It may be worn in clinical, educational, and everyday settings without drawing unwanted attention, offering both safety and discretion.

This invention discloses an auxiliary diagnostic method and system for autism based on a dual-person brain functional connectivity map and graph attention network. It comprises a dual-person fNIRS hyperscanning data acquisition module, a preprocessing and graph construction module, and an edge-weighted enhanced graph attention network classification module. The system has the following technical features: synchronously acquiring brain activity signals of the subject and examinee during social interactions using hyperscanning technology; constructing a dual-person brain functional connectivity map including nodes in both brain regions and the strength of inter-brain connections; and dynamically aggregating and learning node features and edge weights in the graph using an edge-weighted enhanced graph attention network. This invention can objectively capture abnormal inter-brain synchronization in autistic individuals during real social interactions, providing automated, rapid, and quantifiable auxiliary diagnostic results, effectively improving the objectivity and accuracy of diagnosis, and reducing reliance on professional clinical experience.

This invention discloses a method and system for early autism screening based on fNIRS and action feature bimodal fusion, comprising a neural signal acquisition module, a behavioral video acquisition module, a brain network analysis unit, an action analysis unit, and a multimodal fusion decision unit. The brain network analysis unit constructs a dynamic brain functional connectivity map and introduces a graph attention network to automatically learn the importance of key brain regions and their connections. The action analysis unit uses the AlphaPose algorithm to extract key point sequences of the human body and combines bidirectional long short-term memory networks to model action temporal dependencies. The multimodal fusion decision unit employs an attention-based decision-level fusion mechanism, adaptively weighting the classification probabilities of the two branches. This invention achieves multidimensional information complementarity and intelligent fusion for autism by fusing brain signals and behavioral action features, exhibiting strong screening objectivity, high interpretability, and excellent classification accuracy, providing an efficient and automated solution for early autism screening in primary healthcare settings.

This invention discloses a method and system for autism assessment using near-infrared spectral imaging and eye-tracking, relating to the field of autism risk assessment technology. The key technical points include the following steps: collecting the age, developmental level, and past medical history of suspected autism patients to generate autism patient profiles; establishing personal information files; collecting near-infrared spectral imaging data and eye-tracking data of the patients; screening abnormal correlation data of potential autism pathological features to obtain correlation data to be assessed; extracting the functional coupling characteristics, temporal synchronization, and intensity attenuation patterns of abnormal correlations in the correlation data to be assessed; and determining whether it is necessary to perform scheme fusion processing on the correlation data to be assessed from different testing schemes based on the functional coupling characteristics and temporal synchronization. The effect is that it effectively captures the specific pathological characteristics of patients, avoids the problem of a uniform testing paradigm masking individual differences, and further improves the accuracy and specificity of the assessment.

This invention discloses an upper limb rehabilitation training device for autistic patients, comprising a support assembly, a training mechanism, a resistance loading module, a human-computer interaction panel, and a control module. The support assembly provides structural support and allows for spatial adjustment of the training position. The training mechanism, mounted on the support assembly, supports the patient's upper limb and guides its movement. The resistance loading module is connected to the training mechanism to apply adjustable resistance. The human-computer interaction panel has a display screen for showing guided animations. The control module is communicatively connected to the training mechanism, the resistance loading module, and the human-computer interaction panel. The control module is configured with an active guidance mode and an resistance mode. The active guidance mode actively guides the patient's movement, while the resistance mode performs resistance training. This device employs a two-stage training strategy—first establishing motor memory and then progressively increasing resistance—which can reduce patient resistance and the likelihood of agitation while ensuring training effectiveness.

This invention discloses a dual-target transcranial alternating current stimulation method, belonging to the technical field of EEG / neuroelectric stimulation control. It involves identifying two brain regions associated with core autism symptoms as joint stimulation targets based on brain functional connectivity analysis. By applying alternating current signals of specific frequency and intensity to corresponding locations on the scalp, abnormal neural rhythms and long-distance functional connectivity are synchronously modulated, thereby improving patients' social communication impairments and repetitive stereotyped behaviors. This method employs standardized scalp localization and fixed stimulation parameter design, featuring strong non-invasiveness, high safety, good repeatability, and ease of operation. It can improve the targeting and stability of neuromodulation without increasing treatment risks, making it suitable for clinical rehabilitation and auxiliary intervention scenarios, and possessing good application prospects and promotional value.

This invention relates to the technical field of behavioral analysis of children with autism, and provides a method and system for collecting daily behavioral data of children with autism. The method includes: real-time acquisition of triaxial acceleration and triaxial angular velocity from an inertial measurement unit as raw data; extraction of feature data from the raw data; judgment of the physical consistency of the raw data based on the feature data, distinguishing between real limb movement signals and sensor relative motion signals; decomposition of the raw data into a first information stream and a second information stream; identification of behavioral patterns of limb movements in children with autism based on the first information stream; extraction of features from the second information stream to obtain second information features; the second information features characterizing the intensity of sensor relative motion corresponding to the sensor relative motion signal; calculation of a behavior intensity index based on the second information features; and output of the behavior pattern and behavior intensity index. This invention improves the accuracy of collecting daily behavioral data of children with autism.

This invention discloses an autism-assisted diagnostic method and system based on gene pathway mapping information, belonging to the interdisciplinary field of bioinformatics and machine learning. The invention first reads and preprocesses raw sequencing data to obtain a standardized differentially expressed gene matrix; then, it introduces pathway function and topological information to construct a pathway topological adjacency matrix, and obtains gene pathway features by dimensionality reduction, graph signal propagation, and feature encoding of the pathway feature matrix; subsequently, it performs initial training of a multimodal fusion network on the aforementioned two matrices; then, it selects Top K key genes based on gene importance scores and performs secondary training in conjunction with gene pathway features; finally, it inputs the gene expression levels of the subject to be tested and outputs the autism-assisted diagnostic classification results. By introducing gene pathway mapping as prior knowledge, this invention constructs a multimodal fusion network that combines biological interpretability and high robustness, which can improve the accuracy of autism diagnosis based on a small number of key features.

The application provides an autism prediction model based on blood microorganisms and application thereof. The prediction model takes blood microorganisms as markers, and predicts the risk of autism of a blood sample through the decrease of a blood microorganism one detection rate or relative abundance, or the increase of a blood microorganism two detection rate or relative abundance. The blood microorganism one comprises Xanthobacteraceae bacterium, Pseudomonas sp.3J6, Rhodococcus equi, Parabacteroides distasonis, Xylella fastidiosa, Enterorhabdus hofmannii, Wolbachia, Yersinia enterocolitica, Borrelia parkeri and Elizabethkingia sp. The blood microorganism two comprises Klebsiella michiganensis and Bdellovibrio sp. The application constructs a model based on blood metagenomic data of 1946 standard four-generation families of autism, fully develops the advantages of blood microorganisms, sensitively and accurately realizes the capture of disease signals, and can be applied to the prediction of autism in the clinic, and realizes the early risk assessment and stratification of diseases.

This invention discloses a gut microbiota-based system for predicting autism in adolescents and a method for building a model, belonging to the field of biomedicine and artificial intelligence. It includes a detection module for acquiring quantitative detection results of preset microbial markers in fecal samples from a donor, said microbial markers including active rumenococci and / or thermophilic streptococci; and a comparison module for comparing the quantitative detection results with preset thresholds to determine whether the adolescent has autism. This invention has good feasibility and accuracy, can effectively assess the risk of autism in adolescents, and provides a new tool for clinical diagnosis.