Abstract
For the rehabilitation of hypertension patients, a feet massage robot was designed. The mechanism structure and its massage process of feet massage robot were determined conforming to the prescription provided by the massage expert. It is one of critical factors for the robot to find and localize the acupoint precisely in order to cure the diseases. By the direct representation, the model of human pelma acupoint is expressed with the vector variables and formal computer language. Considering the distribution of acupuncture area and robot mechanism structure, the discrete sampling data are divided into piecewise curve fitting. By using data analysis and multiple types of function fittings, we propose a vectorization method for the prediction model following the principle of least-squares. This is a simple and easy-to-use method that will be provided for the robot to automaticlly find and localize the pelma acupoint with little real-time computation and storage. Our works also prompt a research cue for the development of Chinese medical standardization.
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