基于PoseNet的盲人按摩机器人穴位识别

Chen Chen, Ping Lu, Siqi Wang, Zijie Li
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引用次数: 1

摘要

针对目前常见的穴位识别是基于神经网络的边缘提取,受人为因素过多的影响,在寻找穴位时存在一定的干扰和误差。本文提出了一种将姿态跟踪算法与骨骼比例测量相结合的新方法,该方法可以充分贴合人体骨骼,为按摩机器人的穴位识别提供新的思路,提高其准确性和效率。用Python对上述方法进行仿真,实现按摩机器人自动找穴的功能。结果表明,该方法可以在较短的时间内找到更准确、数量更多的穴位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PoseNet Based Acupoint Recognition of Blind Massage Robot
In allusion to the current common acupoint recognition is based on the edge extraction of neural network, which is affected by too many factors of human, there are certain interferences and errors in finding acupoints. This paper put forward a novel method combining posture tracking algorithm with proportional bone measurement, which can fully fit the skeleton of human body to provide a new idea for acupoint recognition of massage robot, and improve its accuracy and efficiency. The above method is simulated in Python to realize the function of massage robot to find acupoints automatically. The result shows that it takes less time to find more accurate and more quantities acupoints.
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