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基于深度学习和解剖学英寸测量的机器人穴位定位方法。

A Combined Deep Learning and Anatomical Inch Measurement Approach to Robotic Acupuncture Points Positioning.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2597-2600. doi: 10.1109/EMBC46164.2021.9629761.

Abstract

Acupuncture therapy is one of the cornerstones in traditional Chinese medicine. It requires rich experiences from Chinese medicine practitioner. However, repeatability among different practitioners are low. Meanwhile, there is a large variety of skin conditions in terms of color, diseases, size, etc. In recent year, deep neural network for acupuncture point detection is proposed. However, it is difficult to localize multiple acupuncture points. In this paper, a high repeatability robot with a new approach of acupuncture points positioning is proposed which can be adaptive to variety skin conditions and achieve multiple acupuncture points' localization.Clinical Relevance- This system can provide identical acupuncture therapy to different patients. Thus, the quality of the therapy can be practitioner independent. Furthermore, the machine operation is simple therefore manual error can be reduced significantly. As the result, the efficiency and accuracy of therapy can be increased.

摘要

针灸疗法是中医的基石之一。它需要中医从业者具备丰富的经验。然而,不同从业者之间的可重复性较低。同时,皮肤状况在颜色、疾病、大小等方面也存在很大的差异。近年来,人们提出了用于针灸穴位检测的深度神经网络。然而,这种方法很难对多个穴位进行定位。在本文中,我们提出了一种具有新穴位定位方法的高重复性机器人,可以适应多种皮肤状况,并实现多个穴位的定位。临床相关性-该系统可以为不同的患者提供相同的针灸治疗。因此,治疗质量可以与医生无关。此外,机器操作简单,因此可以显著减少人为错误。结果,治疗的效率和准确性都得到了提高。

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