7 results about "Tongue coating" patented technology

1. The name of the design product: oral cavity cleaner. 2. The use of the design product: for cleaning the oral cavity, cleaning the tongue coating and dirt. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.

This utility model discloses an oral cavity and tongue coating cleaning device, relating to the field of tongue coating cleaning technology. It includes a handle, with a mounting plate fixedly connected to the center of the handle's interior. A motor is fixedly mounted at the upper center of the mounting plate, and the motor's output end passes through the upper side of the mounting plate and is fixedly connected to a fixing plate. A connecting rod is fixedly connected to the lower right end of the fixing plate, and a spherical sliding block is fixedly connected to the lower side of the connecting rod. A sliding plate is slidably connected to the lower end of the handle's interior. A sloping groove is formed at the upper center of the sliding plate, and a lifting rod is fixedly connected to the lower center of the sliding plate. A spring is sleeved on the surface of the lifting rod. This utility model, by incorporating a motor, fixing plate, connecting rod, spherical sliding block, sliding plate, sloping groove, lifting rod, spring, and soft brush, effectively improves the cleaning efficiency of the device, ensuring that the tongue coating is thoroughly cleaned and effectively protecting human health.

1. Name of the product in this design: Tongue brush. 2. Purpose of this product design: For cleaning the tongue coating. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

1. Name of the designed product: packing tube (Bai Baoli packing design DA). 2. Use of the designed product: for packing of tongue coating paste. 3. Design points of the designed product: in the combination of shape, pattern and color. 4. Picture or photo best indicating the design points: front view. 5. The claimed design contains color.

This invention discloses a method, system, device, and storage medium for constructing an intelligent diagnostic model for TCM tongue imagery, addressing the shortcomings of traditional tongue diagnosis, such as strong subjectivity, difficulty in quantification, and the crude feature extraction, weak integration with TCM theory, and lack of personalized intervention in existing AI systems. Through structured guidance, it achieves a closed-loop health management process encompassing tongue image collection, tongue coating localization, multi-dimensional feature extraction, constitution identification, and personalized dietary intervention. High-precision segmentation of the tongue and tongue coating, along with structured extraction of multi-dimensional tongue image features, enables high accuracy in constitution identification, generating personalized dietary recommendations and dynamic health management, thus improving the objectivity, repeatability, and clinical applicability of TCM tongue diagnosis. Users only need to take a picture of their tongue; the system outputs a complete analysis report within seconds, achieving "diagnosis upon tongue image capture." This is applicable to diverse scenarios such as home self-examination, community health monitoring, and remote TCM consultation, promoting the widespread adoption of TCM tongue diagnosis technology.

This invention relates to the fields of oncology diagnosis, prediction, and assessment, and particularly to a tumor prediction system, method, and application based on tongue coating microorganisms. The system includes: a microbial information acquisition module configured to acquire tongue coating microbial information of a test sample; and a data processing module configured to obtain the probability that the test sample is tumor-positive by predicting the probability of a positive result based on discriminative features of the tongue coating microbial information obtained through automatic learning. The system automatically predicts the probability of different test samples being tumor-positive based on the abundance of different species and genera in the tongue coating microorganisms, thus providing an economical, non-invasive, efficient, and accurate early tumor screening strategy.