3 results about "Human brain" patented technology

The invention discloses a rat acceleration and deceleration brain trauma striking system which comprises an experimental platform, a striking module, a striker module, a positioning module and an acceleration and deceleration trauma switching module. The positioning module is longitudinally and perpendicularly arranged on the experimental platform, the striking module is transversely and perpendicularly arranged on the positioning module, the striking module is placed on the experimental platform, the striker module is arranged at the position, arranged between the positioning module and the striking module, of the experimental platform, and the acceleration and deceleration trauma switching module is arranged on the side edge, longitudinally and perpendicularly corresponding to the striking module, of the experimental platform. Compared with the prior art, the system can precisely manufacture a rat brain trauma model, the repeatability is good, the operation is easy, a rat does not easily die, the acceleration brain trauma model and a deceleration brain trauma model can be manufactured, trauma grading can be carried out on the manufactured models, a matched group of a brain opening cavity and a brain non-opening cavity can be manufactured, and a large amount of support can be provided for research for the human brain trauma.

The invention provides an Alzheimer's disease detection device and computer equipment, and relates to the field of medical disease detection. According to the application, a brain network constructionmodule constructs a to-be-detected brain network corresponding to a to-be-detected brain; a characteristic parameter calculation module calculates a network structure characteristic parameters of target frequent sub-graphs at the to-be-detected brain network corresponding to the target characteristic parameter type, wherein the target feature parameter types corresponding to different target frequent sub-graphs comprise any one or combinations of sub-graph local clustering coefficients, sub-graph importance scores and sub-graph local importance scores; a characteristic parameter classification module inputs the calculated network structure characteristic parameters into a brain detection model to perform Alzheimer's disease characteristic classification; and therefore, under the conditionthat the human brain structure characteristics with high matching degree corresponding to the brain to be detected are obtained, a high-precision Alzheimer's disease diagnosis result is obtained, andthe artificial participation degree in the diagnosis process is reduced.