7 results about "Neurological function" patented technology

Testing methods for evaluating visual and neurological functions of a human or animal subject that involve conscious perception. The tests include a training phase, a practice phase, and a visual rivalry phase for detecting binocular rivalry or multistate competition. The design of the testing methods offers simple, rapidly administered, nonverbal visual testing with high time resolution and access to changing conscious perceptual states of the test subject. The methods also make possible the collection of a large amount of data in a short time for analysis of the subjects visual function and brain function, and can be used in the diagnosis of many medical conditions.

A method for assessing driver ability is presented, belonging to the field of driving behavior detection and assessment technology. It addresses the technical problems of existing driving ability assessment technologies, such as limited assessment dimensions and the lack of specific models for individuals with impaired neurological function. By constructing a multimodal data acquisition platform involving humans, vehicles, and the environment, driving behavior data is collected under preset simulated driving conditions. Statistical feature values ​​are extracted, driving behavior distribution feature values ​​are constructed, and cluster analysis and classification neural networks are used to complete the driving ability level assessment. Corresponding driving suggestions and auxiliary prompts are automatically output, thereby achieving a scientific, systematic, and multidimensional assessment of the ability of individuals with impaired neurological function to regain driving ability.

The invention relates to an NIHSS score diagnosis system based on artificial intelligence and a system establishment method thereof, and belongs to the technical field of artificial intelligence. The method comprises the following steps: S1, acquiring voice, face images, limb movement and eyeball movement data of a patient through a testing device; s2, analyzing the voice response by using a voice recognition module, and matching the voice response with a standard answer; s3, extracting facial expressions, pupil sizes, limb movement amplitudes and ataxia coordination features through an image processing module; s4, mapping the feature data into each item score based on an NIHSS scoring rule, and calculating a total score; and S5, outputting a scoring result and a corresponding nerve function defect severity level. Quantitative measurement of various examination results is improved, standardization of NIHSS scores is realized, subjectivity of doctor operation is reduced, workload of doctors is reduced, more accurate treatment decisions are further provided for patients, and accurate development of clinical research is promoted.

The invention relates to the field of medical information processing, in particular to a stroke home rehabilitation guidance method and system based on multi-dimensional classification. The method comprises the following steps: acquiring basic conditions of a stroke patient, and classifying disease characteristics, neurological function defect parts, severity and complications to form a classification result; executing patient group mapping based on a classification result, and establishing corresponding key monitoring related indexes; change collection and change analysis are carried out according to key monitoring related indexes, and stage rehabilitation scheme suggestions are generated; and carrying out abnormal judgment and online guidance according to the stage rehabilitation scheme suggestions, forming adjustment suggestions, and writing back the adjustment suggestions. According to the invention, the classification result is used as an organization basis throughout the whole process, so that a consistent closed-loop processing link is formed by monitoring, analysis, guidance and write-back, and the continuity, traceability and collaborative stability of the scheme generation and adjustment process in the stroke home rehabilitation guidance process are improved.

The invention discloses a neural function precise rehabilitation training instrument based on multi-modal intelligent feedback, which comprises a bottom plate, supporting rods are fixedly arranged at the two ends and the middle end of the bottom plate, a straight rod is fixedly arranged on one side of the top of each supporting rod, a seat plate is mounted on the top of each straight rod, a bent rod mechanism is fixedly arranged on the side part of each straight rod, and the bent rod mechanisms are fixedly arranged on the side parts of the bent rod mechanisms. A first winding mechanism is fixedly arranged on the inner wall of the upper end of the rod bending mechanism, a first pull rope is wound in the first winding mechanism, first pull belts are installed at the two ends of the first pull rope correspondingly, a backup plate is fixedly arranged on one side of the seat plate, and a pedal machine is fixedly arranged in the middle of the top of the bottom plate; the other side of the top of the bottom plate is fixedly provided with an inclined rod, the top of the inclined rod is fixedly provided with a vertical rod mechanism through a mounting block, and the problems that most of existing rehabilitation training devices can only conduct independent training on upper limbs or lower limbs, four-limb linkage is difficult to achieve, and the rehabilitation efficiency is low are solved.

The application discloses a kind of spinal cord injury analysis method and system based on medical image, belong to image analysis technical field, obtain the MRI image of target object at multiple time points and carry out registration and normalization processing, construct time series image set;Spinal cord and injury area are extracted using spinal cord structure guided dynamic segmentation network;The time sequence deformation path of injury area is constructed based on morphological tracking algorithm;Extract high-order morphological features including curvature change rate, edge contour jump value and spinal cord compression rate;Features and neural function score are modeled in two domains, and a structure-function coupling model is trained;The model is used to predict the functional status of new patients, identify risk areas, and output rehabilitation recommendations. This method has strong predictive power, high accuracy, and significant clinical assistance value.

The invention belongs to the technical field of rehabilitation instruments, and particularly relates to a rigid-flexible coupled intelligent pneumatic rehabilitation glove. In order to solve the problems of low directional bending precision, insufficient output force and the like of the pneumatic rehabilitation gloves, a pneumatic network layer of the pneumatic actuator adopts a hyperbolic structure design, and an asymmetric gradually-broadened opening design generates a pressure gradient effect, so that high-precision directional bending is realized. The pneumatic actuator adopts the rigid-flexible coupling design, the limiting layer is embedded into the hard fish tail bone, the rigidity is changed through the rigid-flexible coupling composite beam unit of the limiting layer, and the joint torque and the fingertip output positive pressure are effectively improved. By switching positive pressure and negative pressure, high-precision large-output-force directional flexion and extension rehabilitation actions of the hand can be realized. Passive multi-mode training, mirror image training and active rehabilitation training based on multi-channel electromyographic signal motion intention recognition are combined, so that neurological function recovery of a patient is better achieved.