20 results about "Autistic disorders" patented technology

The invention discloses an autistic child emotion regulation system integrating electroencephalogram feedback and art, and relates to the technical field of medical intelligent rehabilitation. An emotional state decoding module; a dynamic generation type art interaction guiding module; a closed-loop feedback regulation and control module; and an adaptive optimization module. According to the method, deep fusion of physiological signal monitoring and artistic emotion expression is realized, scientificity and effectiveness of emotion regulation intervention of the autistic children are remarkably improved, participation willingness and compliance of the children are effectively improved, personalized iteration and accurate regulation of the intervention process are realized, limitation of traditional single-mode intervention is broken through, and the method is suitable for popularization and application. Not only is the objectivity of emotion recognition and the pertinence of art guidance enhanced, but also an individualized rehabilitation path is formed through long-term memory map construction, and an intelligent, quantifiable and sustainable new emotion regulation normal form is provided for autistic children.

FIELD: neurology; psychiatry.SUBSTANCE: used as a non-pharmacological therapy for autism spectrum disorders in children. The method includes a set of procedures: interval hypoxic-hyperoxic training (HHT), hyperbaric oxygenation and ozone therapy. HHT consists of alternating inhalations of a hypoxic mixture with an oxygen content of 9 to 16 vol.% and a hyperoxic mixture with an oxygen content of 32 to 40 vol.% for a total duration of 45-50 minutes under the control of cardiovascular system parameters. Hyperbaric oxygenation is performed in a pressure chamber under a pressure of 1.3 atmospheres of 100% oxygen mixture, flow of 10 liters per minute, for 45 minutes using a mask. Ozone therapy is performed by rectal insufflation with an ozone-oxygen mixture with an ozone concentration of 85 μg / ml in a volume of 20–30 ml or by intravenous administration of a physiological solution enriched with ozone with an ozone concentration of 85 μg / ml at a rate of 200 ml per 100 ml of physiological solution. The procedures are carried out daily for 12 days.EFFECT: method is effective and has a positive impact on the patient’s condition.1 cl, 1 dwg, 3 ex

The invention relates to the crossing field of target detection and emotion recognition, in particular to an autistic child facial expression recognition method based on deep learning. Comprising the following steps of: embedding three-dimensional attention (Tri-attention) behind a C3k2 module of a YOLOv11 backbone network so as to model an interactive relationship among three dimensions of height, width and channel in parallel and enhance response to key expression areas such as eyes, mouth corners and the like; three-dimensional attention (Tri-attention) is introduced into the multi-scale feature output end of the neck network again, and effective positioning and background noise suppression of a small-scale face under a complex background are achieved; respectively training and verifying the YOLOv11-TA model by using the public data set and a self-built autistic child data set, and outputting a detection frame of each face and an expression category thereof; by comparing various indexes of the original YOLOv11 and YOLOv11-TA on various data sets, the accuracy and robustness of expression recognition of the autistic children are remarkably improved by the method according to actual verification.

The present invention is directed to the use of antiviral agents, in particular valomaciclovir stearate and its polymorph Form A, as well as H2G (omaciclovir) to treat multiple sclerosis in combination with other agents, as well as the use of these agents to treat diseases and conditions such as chronic mononucleosis, long COVID, chronic fatigue syndrome, fibromyalgia, Crohn's disease, ulcerative colitis, rheumatoid arthritis, systemic lupus erythematosus, Graves' disease, Alzheimer's disease, mesial temporal lobe seizures, Epstein-Barr-virus-linked autism, or an Epstein-Barr-virus-linked cancer.

The present invention relates to the field of artificial intelligence and data processing technology, and in particular to a method for evaluating the effect of an executive intervention based on deep learning, which is as follows: recording the heart rate signals of autistic children during intervention task training through a wearable heart rate monitoring device; preprocessing the collected heart rate signals; constructing a data set and dividing it into a training set, a validation set, and a test set; performing dynamic time segmentation and adaptive noise suppression on each sample data in the data set; constructing an executive intervention effect evaluation model based on deep learning, inputting the denoised training set into the model for training, and verifying the performance indicators of the model through the validation set; inputting the data in the test set into the trained model to obtain the final evaluation results. The present invention can objectively estimate the effect of the intervention and assist manual judgment by analyzing and processing the heart rate signals reflecting psychological load, cognitive engagement, and emotional fluctuations.

The invention discloses a method for improving autism behaviors through Npas4 expression and overexpression in a cat chat syndrome model, and belongs to the technical field of animal model construction. Selecting SD wild rats and CdCS model rats, and normally feeding and breeding the rats; the method comprises the following steps: measuring the protein concentration by adopting a BCA method, then carrying out Western Blot, then carrying out brain stereotactic injection, and finally carrying out behavioral testing. According to the invention, a CdCS rat model is established by using a CRISPR-Cas9 technology, and the model shows cognitive and social behavior disorders and medial prefrontal cortex (mPFC) neuron dendritic abnormality; in addition, an abnormally expressed gene is found in the model mouse, the research focuses on Npas4, and a new insight is possibly provided for disease treatment.

The present application relates to the cross field of target detection and emotion recognition, and particularly relates to a facial expression recognition method for autistic children based on deep learning. The method comprises the following steps: embedding a three-dimensional attention (Tri-Attention) after a C3k2 module of a YOLOv11 backbone network to model the interaction relationship among height, width and channel dimensions in parallel, and enhancing the response to key expression regions such as eyes and corners of the mouth; introducing the three-dimensional attention (Tri-Attention) again at the multi-scale feature output end of the neck network to realize effective positioning of small-scale faces in a complex background and suppression of background noise; training and verifying the YOLOv11-TA model by using a public data set and a self-built autistic children data set respectively, and outputting the detection frame and expression category of each face; and comparing various indexes of the original YOLOv11 and the YOLOv11-TA on multiple data sets, and actually verifying that the method significantly improves the accuracy and robustness of the expression recognition of autistic children.

The application discloses a kind of adolescent autism intestinal microorganism marker and application thereof, belong to the field of biological medicine.The microorganism marker includes one or more of Ruminococcus gnavus, Streptococcus thermophilus, Streptococcus salivarius, Butte's intestinal bacillus, pet big anaerobic clavulanic acid bacteria and Prevotella pittmanniae.The application provides a kind of product (such as kit), including detection reagent for detecting the relative abundance of the microorganism marker.The product provided by the application has good feasibility and accuracy, and can effectively evaluate whether adolescent has the risk of autism, provides a new tool for clinical diagnosis.

The invention provides an autistic patient dietary behavior associated data analysis method and system, relates to the technical field of data analysis, and aims to effectively identify potential trigger events and establish a behavior stability benchmark by integrating multi-dimensional time sequence data, establishing a behavior stability benchmark and performing multi-dimensional difference comparison during behavior deviation. And potential triggering factors inconsistent with the safety mode are identified when the behavior deviates, so that the accuracy and the reliability of analysis are improved.

The present invention relates to the field of auxiliary diagnosis and treatment, and in particular to an analysis method for auxiliary diagnosis and treatment of autistic children. The present invention performs pre-detection on a target object and stores detection data to analyze the target object's motion feature representation, determine the target object's motion feature feedback degree, and perform auxiliary diagnosis and treatment analysis, including: adjusting the image acquisition accuracy of the image acquisition device for the target object, calling the video record in the target object's review case, identifying emotional gaze features, limb movement amplitude, and the change ratio of feature matching parameters relative to the pre-detection based on the video record, and comparing them with expected control data determined based on a pre-stored intervention diagnosis and treatment plan to determine whether the feature matching standard is met; generating a recommended number of re-examinations based on the motion feature representation, and outputting the results of the auxiliary diagnosis and treatment analysis through an output end. The data analysis results are accurate and reliable, can provide doctors with auxiliary diagnosis and treatment data support, and improve diagnosis and treatment efficiency.

A targeted acupuncture treatment method for children with autism belongs to the field of medical care, and comprises a sound induction ear acupuncture method, a long-acting eye stimulation opposite pressing acupuncture method and a liver-spleen-kidney simultaneous acupuncture method. The system can improve the core symptoms of the autistic children (3-12 years old), such as not listening to instructions, eye contact parallax, inattention, diet singleness, emotion awareness, hyperactivity and the like, realizes targeted intervention through multi-module collaborative acupuncture, and is suitable for pediatrics of medical institutions, children rehabilitation centers and professional acupuncture clinics.

Modulators of intracellular chloride concentration are disclosed. The present invention relates in particular to compounds of Formula Ia, Ib and Ic, pharmaceutical compositions comprising the compounds of Formula Ia, and their use in the treatment or prevention of pathological conditions associated with the delivery of depolarized GABA, including, for example, Down's disease and autism.

The application discloses a kind of composite nutrient composition and its application in intervention autism and mental retardation, the composite nutrient composition is composed of composite vitamin, mineral, enterobacterium, apple fruit powder and the substance for improving taste;Wherein, the procyanidin B1 content in the apple fruit powder is more than 30mg / kg, the composite nutrient composition of the application can effectively improve the repetitive stereotyped behavior of autistic children, the degree of anxiety, the degree of cognition, and social skills, and effectively improve the intestinal flora imbalance phenomenon of autistic children.It can also effectively improve the cognitive ability of children with mental retardation.

A pharmacological method for treating the expressive language deficit in an autistic human child or adult is provided. A therapeutically effective dose of a succinimide anticonvulsant, e.g., ethosuximide, methsuximide, phensuximide, or a pharmaceutically acceptable salt thereof, is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer. Language gains are retained even after treatment is discontinued.

The present invention relates to dosing regimens and methods of using LY3154207, also described as 2-(2,6-dichlorophenyl)-1-[(1S,3R)-3-(hydroxymethyl)-5-(3-hydroxy-3-methylbutyl)-1-methyl-3,4-dihydroisoquinolin-2 (1H)-yllethanone, and / or pharmaceutical compositions thereof, for treatment of dopaminergic central nervous system disorders. Dopaminergic CNS disorders of the present dosing regimen methods include Parkinson's Disease, Alzheimer's Disease, Lewy body dementia (LBD), Vascular Dementia, Schizophrenia, ADHD, Depression, Autism, chronic musculoskeletal pain, fibromyalgia, cognitive impairment disorders, sleep disorders, excessive daytime sleepiness, narcolepsy, shift work disorder, traumatic brain injury, chronic traumatic encephalopathy, obesity and appetite regulation, mood disorders, lethargy, apathy, and addiction disorders.

This application relates to the field of data processing technology, and discloses a method, system, and medium for identifying autistic behaviors in children based on data analysis. The method includes: collecting and preprocessing multimodal behavioral data of children; extracting nonlinear features to obtain a time-series feature matrix; identifying repetitive behavioral patterns using a three-dimensional convolutional network; analyzing temporal changes in behavior using a temporal convolutional network; fusing multiple feature representations to obtain a comprehensive feature vector; and applying a multi-classifier system to identify autistic behavior types and assess severity. By extracting nonlinear time-series features, constructing a deep spatiotemporal feature extraction network, designing a feature fusion mechanism, and integrating a multi-classifier system, this invention overcomes the limitations of existing technologies involving single modality, linear features, and single algorithms, thereby improving the accuracy and interpretability of autistic behavior identification.

The invention discloses an infantile autism family psychological intervention system and an infantile autism family psychological intervention method. Comprising a family psychological state dynamic monitoring module, a multiple psychological therapy technology integration module, a physiological collaborative rehabilitation intervention module, a family interaction mode optimization module, a personalized intervention scheme generation module, an intervention effect real-time evaluation and dynamic adjustment module, a family support resource integration module and a child behavior observation and feedback module. By monitoring the family psychology and interaction state in real time, various treatment technologies and resources are integrated, and a personalized intervention scheme is generated. The method comprises the steps of baseline evaluation, scheme making, intervention implementation, dynamic adjustment, follow-up visit consolidation and the like, focuses on improvement of the psychological state of parents and a family interaction mode, creates a supportive rehabilitation environment for autistic children, and has a remarkable intervention effect through practice verification.

The subject matter described herein includes methods and systems for predicting and preventing negative behaviors with learning and AI algorithms. According to one method, physiological data of a user is measured. For example, using sensors located on the user. A stress level of the user is determined based on the measured physiological data. An intervention is then determined for adjusting the stress level of the user in response to the stress level being at least one of outside or nearing outside of a baseline range of the user. According to one system, at least one sensor measures physiological data of a user. An analysis device, such as a mobile device or remote server, determines a stress level of the user based on the measured physiological data and determines an intervention for adjusting the stress level of the user in response to the stress level being outside or nearing outside of a baseline range of the user.

Provided is a Bifidobacterium lactis. The Bifidobacterium lactis is Bifidobacterium animalis subsp. lactis BL-11, and the preservation number of the Bifidobacterium animalis subsp. lactis BL-11 is CGMCC No. 20847. The provided Bifidobacterium animalis subsp. lactis can improve intestine metabolism disorder and normalize the composition of intestine microbiome so as to improve height, suppresses obesity, promote infant and youth physical development and mental development, and prevent and treat mental disorders, said mental disorders including anxiety, depression, attention-deficit / hyperactivity disorder, autism, schizophrenia, hepatic encephalopathy, anorexia, Tourette syndrome, and Asperger syndrome.