Hand physiological information detection method

Abstract

The invention relates to a hand physiological information detection method, which comprises the following specific steps of: detecting hand integrity; detecting wrist flexibility; finger flexibility detection. The invention provides a hand physiological information processing method based on a skeleton key point dynamic identification technology. A hand in motion is scanned in real time, and computer analysis is carried out through a unique algorithm and a model, so that hand information can be analyzed and processed quickly and accurately, data analysis is carried out on related information such as whether hand skeleton key points, hand wrist and upper limb functions are perfect and hand integrity and hand coordination, and accurate integrity and flexibility detection results are given.

Description

technical field [0001] The invention relates to a hand physiological information detection and processing method based on the dynamic recognition technology of bone key points, belonging to the technical field of video image processing Background technique [0002] The "Regulations on the Application and Use of Motor Vehicle Driving Licenses (2016 Edition)" requires the driver's license applicants to have hands as follows: the thumbs of both hands must be sound, the other fingers of each hand must have three fingers, and the motor functions of the limbs and fingers should be normal. Those who have incomplete finger tips or have three healthy fingers on their left hand and have intact palms of both hands can apply for a motor vehicle driver's license for a permitted type of small car, small automatic transmission car, low-speed truck, or three-wheeled car; Those who have motor functions but are able to sit and stand independently, and whose upper limbs meet the requirements, ...

AI Technical Summary

Problems solved by technology

In machine detection, the current common detection technology is to use the hand photo image matting technology to determine the integrity of the hand. When the hand is wearing gloves, accessories, large-area color interference, wearing artificial limbs, etc., the measurement data will be There will be inaccuracies, and the dexterity of the hand cannot be directly judged. Manpower is required for auxiliary detection, which increases the time, manpower, and material resources of the detection.

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