6 results about "Behavior disorder" patented technology

Systems and methods for predicting problem behavior in individuals with developmental and behavior disabilities. A plurality of sensors are configured to collect multimodal data signals of a subject individual including a wearable upper body motion sensing device with a plurality of inertial measurement units (IMUs). An electronic controller is configured to receive output signals from each of IMUs and to model an upper body position of the subject individual based on the output signals from the IMUs. A trained machine-learning model is then applied by providing an input data set that includes multimodal signal data (e.g., including signal data from at least one IMU) and / or features extracted from the multimodal signal data. The machine-learning model is trained to produce as output an indication of whether a precursor to the problem behavior is detected and, in response to detecting the precursor, a notification (or alarm) is generated.

The invention discloses an AI intelligent cooperative control method based on an IQL algorithm, and relates to the technical field of artificial intelligence control, and the method comprises the following steps: obtaining a local observation state sequence of a target agent in a continuous control period, dividing the local observation state sequence into a plurality of time windows with the same time length, extracting observation characteristic variables in each time window to form a basic observation vector group; by constructing a disturbance index system and introducing a time decoupling control mechanism, joint quantitative expression of local state disturbance and environmental behavior complexity is realized, and by means of dynamic rhythm adjustment and micro-amplitude peak shifting execution, the problems of multi-agent synchronization conflict and strategy resonance are effectively suppressed, the risk of path blockage and behavior disorder is reduced, and the method is suitable for large-scale popularization and application. And the cooperation consistency and the operation stability of the multi-agent system in a dynamic interference environment are obviously improved.

The invention discloses a personality self-adaption-based personalized communication scheme generation method and device, and the method comprises the steps: receiving a communication scene inputted by a user, and extracting the personality features of the user and the personality features of an interaction object; according to the personality characteristics of the user and the personality characteristics of the interaction object, a behavior disorder diagnosis report is generated in combination with a personality disorder rule base; generating a scene simulation interaction task according to the behavior disorder diagnosis report, and sending the scene simulation interaction task to the user for interaction; collecting interaction data of finishing the scene simulation interaction task by the user, and comparing the interaction data with risk points in the behavior disorder diagnosis report to obtain a comparison result; and an intervention instruction is generated according to a comparison result, and the non-adaptive behavior or psychological state glide of the user is intervened and corrected in real time according to the intervention instruction, so that a final communication scheme is generated, and the behavior change efficiency and continuous motivation of the user in multiple fields such as interpersonal communication, sales, fitness training, learning and growth and the like are improved.

Described herein are systems and methods used to evaluate individuals such as children for behavioral disorders, developmental delays, and neurological impairments. An exemplary method includes receiving input data of an individual related to a behavioral disorder, neurological impairment, or developmental delay, and evaluating the input data using an evaluation module comprising at least one machine learning model, thereby generating an evaluation result, where the machine learning model comprises one or more decision threshold hyperparameters that differentiate between a positive evaluation, negative evaluation, and an indeterminate evaluation with respect to a presence or an absence of the behavioral disorder, neurological impairment, or developmental delay.

The invention discloses an exosome-like nano-vesicle derived from rhizoma acori graminei as well as a preparation method and application of the exosome-like nano-vesicle. The rhizoma acori graminei-sourced exosome-like nano-vesicle contains rich bioactive components, has excellent biocompatibility, brain targeting property and cross-biological barrier property, and is beneficial to enhancing the treatment effect of brain diseases. After oral administration or caudal vein injection, the exosome-like nano-vesicle derived from the rhizoma acori graminei can enter the brain across the blood brain barrier, the behavioral disorder of AD model mice is improved, the disease development of Alzheimer's disease cognitive impairment accompanied by depression is improved through the effects of relieving neuron injury, neuroinflammation and synaptic injury, and the development of Alzheimer's disease cognitive impairment accompanied by depression is promoted. Wide application prospects are shown.

A detecting method for a behavior disorder event during rapid-eye-movement sleep is provided. The detecting method includes: collecting a heart rate value and a motion value of a user per epoch within a time period; generating a plurality of corresponding sleep condition values by using the motion values, to distinguish epochs into an awake period and a sleep period; transforming the motion values corresponding to the sleep period into a score according to a predetermined rule, to generate a plurality of sleep depth scores, and distinguishing the sleep period into a light sleep period and a deep sleep period by using the sleep depth scores; grouping the heart rate values corresponding to the deep sleep period as a high heart rate group and a low heart rate group; and determining, when the motion values corresponding to the high heart rate group satisfy a condition, that a behavior disorder event happens.