9 results about "Neural function" patented technology

The application provides a personalized rehabilitation path making method and system based on amygdala function evaluation. First, the application obtains multi-modal neural function data of an individual. Second, the amygdala function lateralization mode is determined based on amygdala sub-region functional connection data. Third, the amygdala function lateralization mode is cooperatively analyzed with preset target individual behavior representation data. Finally, the personalized rehabilitation path is generated according to the cooperative analysis result obtained by the analysis. The technical scheme provided by the application not only realizes sub-region level accurate evaluation of amygdala function by integrating multi-modal neural function data and individual behavior representation data, but also generates a highly individualized rehabilitation path with precise coupling of neural activity and rehabilitation training, thereby effectively improving the pertinence and effect of intervention.

This invention provides a head-mounted intelligent wearable neuromodulation and sleep state regulation device and method based on neural coupling tuning and state transfer induction, including a flexible contact array, a state recognition module, a state transfer induction module, a neural coupling modulation module, a stimulation output module, and a feedback optimization module. The system acquires brain state feature vectors and, based on sleep stages and state regulation goals, divides the head into multiple neural functional node regions. Based on the brain state feature vectors, it dynamically generates node combination relationships, node activation sequences, and node collaborative paths. The state transfer induction module controls multimodal stimulation signals to form rhythmic synchronization, phase coupling, and node collaborative regulation, and outputs the signals to the probes corresponding to the target nodes. Simultaneously, it collects feedback signals in real time and dynamically optimizes the topological relationships between nodes and stimulation parameters to achieve closed-loop transfer regulation of brain states between different sleep stages. This invention can improve the individual adaptability, regulation accuracy, and safety of sleep state regulation.

The application relates to the technical field of a brain-computer interface driven wearable adaptive brain-spinal cord synergistic neural regulation system, and particularly discloses a brain-computer interface driven wearable adaptive brain-spinal cord synergistic neural regulation system, which aims to solve the problems of brain and spinal cord regulation device synergistic stimulation, brain signal decoding based on a brain-computer interface, and a closed-loop adaptive neural regulation mechanism. The system comprises a brain-computer interface signal acquisition and decoding module, a multi-modal physiological state sensing module, and an adaptive brain-spinal cord synergistic neural regulation decision and execution module. The system realizes closed-loop adaptive neural intervention by collecting electroencephalogram and electromyogram signals in real time and dynamically generating brain and spinal cord synergistic regulation parameters. The application improves the individualization, precision and continuity of neural function repair, and has wearable integration and safety monitoring capabilities.

The application discloses a kind of based on proprioception guide's brain-computer interface closed loop rehabilitation training system and method, it is related to brain-computer interface technical field, to solve the problem that existing fusion stimulation's brain-computer interface system lacks the individualized rehabilitation training method of stage, guiding, and with promoting central nervous remodeling as basic goal in rehabilitation training, system includes stimulation module and the central control module being connected with stimulation module, the stimulation module applies external stimulation to target muscle group;The central control module is respectively connected with intention decoding module and multi-modal feedback module, the intention decoding module judges whether motion intention characteristic meets standard according to built-in algorithm model;The intention decoding module is connected with electroencephalogram acquisition and processing module, and the electroencephalogram acquisition and processing module real-time acquisition and pre-processes electroencephalogram signal;The technical scheme of the application can enhance the authenticity and effectiveness of motor imagination, promote neural function remodeling.

This invention discloses a novel optical device belonging to the field of sensory intelligence. Its structure and formation method are as follows: it is composed of a large number of precisely arranged optical fibers, with a hammer-shaped form. Its large end face, i.e., the light-incident end face, is a convex or concave curved surface structure, while its small end face, i.e., the light-outceasing end face, is a planar microarray structure of optical fibers or a curved microarray structure of optical fibers. Its main functions are: mimicking the retinal nerve function of human and animal eyes, it can collect light signals in space and transmit them in parallel to a photoelectric conversion array for visual perception signals, forming high-dimensional voxel signals; and it can amplify and reduce these high-dimensional voxel signals for further signal processing by brain-like sensory integrated circuits. This invention also discloses the fabrication methods of this novel optical device, including optical fiber drawing, micro-nano fabrication, and 3D printing.

The present application relates to the technical field of neural information, in particular to a movement disorder treatment analysis method and system based on neural loop feedback, comprising the following steps: dividing functional partitions based on neural loop activity, extracting signal fluctuation and discharge trajectory to identify abnormal intervals, analyzing signal gradient and direction consistency according to candidate set, extracting distribution matrix to analyze uniformity and screen abnormal areas, evaluating deviation calibration level, screening partition adjustment, and outputting neural regulation linkage adjustment data table. In the present application, signal fluctuation and discharge trajectory are extracted based on neural loop activity division and time synchronization analysis, which can accurately identify abnormal intervals, and signal distribution matrix and functional feature analysis are used to strengthen local uniformity evaluation, optimize neural loop response coordination and signal conduction stability, realize accurate positioning and dynamic regulation of movement disorder causes, and ensure the pertinence and consistency of neural function evaluation and regulation.

This invention belongs to the field of biomedical engineering technology. It discloses a stem cell therapy efficacy evaluation system based on brain-computer interfaces and genetic information, comprising: acquiring multi-channel EEG signals and genomic polymorphic site data from patients; constructing a priority mapping matrix for repair needs in target brain regions; extracting micro-functional domain gene neural function coupling strength distribution data; identifying neural plasticity-sensitive regions based on changes in coupling strength gradients; calculating the regulatory enhancement coefficient and migration retardation coefficient of stem cell differentiation signals; constructing a multi-scale pathway synergy map; generating a composite scheme of treatment efficacy characterization parameters based on the map and mapping matrix; monitoring event-related potential waveform features to identify characteristic plasticity response peaks; constructing stem cell therapy efficacy evaluation results; and significantly improving the accuracy of stem cell therapy efficacy evaluation.