3 results about "Safety indicators" patented technology

The invention provides a chronic heart failure patient water intake dynamic regulation and control method based on machine learning, relates to the field of dynamic regulation and control, and improves the individualized level and clinical practicability of water intake management. The method comprises the following steps: firstly, constructing a standard time sequence data set through physiological parameter acquisition and time sequence alignment processing; thirdly, constructing a risk prediction model by adopting a time sequence fusion encoder trained by a meta-learning framework, realizing rapid individualized adaptation, and outputting a liquid retention risk probability value and a basic water intake interval; and finally, based on the risk probability value, in combination with a patient comfort index and a renal function safety index, performing multi-objective decision in the basic water intake interval through adaptive weighted optimization and a reinforcement learning adjustment mechanism, and generating a comprehensive recommended water intake. By integrating the meta-learning framework, the time sequence fusion encoder and the multi-target collaborative optimization mechanism, the accuracy, the safety and the individualized level of water intake management of the chronic heart failure patient are remarkably improved.

The invention discloses an escape path determination method and device, equipment, a medium and a product, and the method comprises the steps: obtaining the position information of each user in a building and the environment information in the building under the condition that an emergency occurs in the building; according to the position information and the environment information of each user, determining area state information of each sub-area in the building; determining a plurality of candidate escape paths of the target user according to the area state information of each sub-area; acquiring safety index data corresponding to the candidate escape paths; scoring the candidate escape paths according to the safety index data to obtain a path score of each candidate escape path; and determining the candidate escape path corresponding to the highest path score as a target escape path. According to the embodiment of the invention, the safety guarantee capability of path planning in an emergency scene can be remarkably improved, and the casualty risk in emergencies such as a fire disaster can be effectively reduced.

This invention relates to the field of stroke hand function rehabilitation technology, and more particularly to a smart training health data assessment system for stroke hand function rehabilitation. The system includes: a data acquisition and mapping module, a spatial filtering module, a spatiotemporal separation module, a template alignment module, a training adjustment module, and a safety monitoring module. The data acquisition and mapping module acquires multi-channel electromyographic signals of the hand and forearm target muscle groups of stroke patients and establishes a mapping between the acquisition area and the target muscle groups. The spatial filtering module performs spatial filtering on the acquired signals. The spatiotemporal separation module extracts spatiotemporal coordination patterns of the hand and adaptively adjusts the number of coordination patterns. The template alignment module spatially aligns the coordination patterns and calculates scores. The training adjustment module adjusts training parameters, and the safety monitoring module monitors safety indicators. In this invention, the system achieves a complete closed loop of health data assessment and training adjustment, improving the problems of disconnect between assessment and training needs and insufficient adaptability caused by traditional single signal acquisition or offline assessment.