Anti-falling method, anti-falling system and anti-falling foot ring
By building a fall database and training an intelligent fall discriminator, and combining the user's physical status, road and environmental information to conduct fall risk analysis, the problems of inaccurate risk assessment and insufficient timeliness of early warning response caused by relying on a single sensor data in the existing technology are solved, and accurate prediction and timely feedback on the user's fall risk are achieved.
CN119848641AInactive Publication Date: 2025-04-18TONGJI HOSPITAL ATTACHED TO TONGJI MEDICAL COLLEGE HUAZHONG SCI TECH
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Patent Information
- Application Number
- CN202411756424.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-03
- Publication Date
- 2025-04-18
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Technical Problem
The existing fall warning system relies on a single sensor data, resulting in insufficient accuracy of risk assessment and early warning response timeliness.
Method used
By dynamically monitoring the physical information and environmental data of the target user, a fall database is built and an intelligent fall discriminator is trained to analyze the fall risk by integrating the user's physical status, road and environmental information, and when the warning conditions are met, a fall warning is issued through the voice education module.
Benefits of technology
Through multi-dimensional data fusion analysis, users' fall risks can be accurately predicted and promptly feedback, and effectively prevent and intervene in fall events.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses an anti-tumble method, an anti-tumble system and an anti-tumble foot ring, and relates to the technical field of protective equipment, and the method comprises the steps: obtaining the body information of a target user through dynamic body monitoring, collecting road and environment perception data, constructing a tumble database, and extracting tumble and non-tumble data sets; training to obtain an intelligent tumble discriminator, carrying out tumble risk analysis by combining the physical state of the target user and the road and environment information, and generating a discrimination result; and when the judgment result meets the early warning condition, the voice propaganda and education module is activated, and a fall early warning is sent to the user in time. The technical problems that an existing fall early warning system depends on single sensor data, and the accuracy of risk assessment and the timeliness of early warning response are insufficient are solved, the fall risk of the user is accurately predicted and fed back in time through multi-dimensional data fusion analysis, and the user experience is improved. The technical effect of effectively preventing and intervening the falling event is achieved.
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