The present invention provides a
skin repair
efficacy evaluation modeling device based on a
machine learning model, which relates to the technical field of
skin repair. The method comprises: a friction module, which is used to apply uniform
friction force on the
skin surface; a scratch module, which is used to make scratches on the surface of a three-dimensional skin model of a
human body; a friction number counting module, which is used to
record the number of frictions; a force control module, which is used to control the
friction force applied to the skin; a speed control module, which is used to control the friction speed on the skin; a scratch control module, which is used to control the length of the scratch generated by friction on the skin; an angle control module, which is used to adjust the scratch angle on the skin; a feedback module, which is used to measure the
erythema index and
hemoglobin content of the skin through a multi-
spectral imaging device; a central control module, which is used to control a force control module, a speed control module, a scratch control module and a
position control module; and a safety protection module, which is used to provide safety protection through an
emergency stop button and a safety guardrail.