上海交通大学机械系统与振动国家重点实验室
纸质出版:2018
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[1]叶林伟,刘洪海.基于超声的厚度提取算法[J].传感器与微系统,2018,37(03):112-114.
YE Lin-wei, LIU Hong-hai. Thickness extraction algorithm based on ultrasound[J]. 2018, 37(3): 112-114.
[1]叶林伟,刘洪海.基于超声的厚度提取算法[J].传感器与微系统,2018,37(03):112-114. DOI: 10.13873/j.1000-9787(2018)03-0112-03.
YE Lin-wei, LIU Hong-hai. Thickness extraction algorithm based on ultrasound[J]. 2018, 37(3): 112-114. DOI: 10.13873/j.1000-9787(2018)03-0112-03.
超声影像具有非侵入、无辐射、实时等特点
在人体肌肉收缩和舒张过程的研究中具有无可比拟的优势
运用超声影像可以实时获取人体组织的数据
从中可以提取肌纤维角度、肌纤维长度、肌肉横截面积和肌肉厚度等生理解剖学信息。提出了一种测量上臂肱二头肌肌肉厚度的方法
包括3个步骤:上肌膜特征点的提取和跟踪;下肌膜特征线的提取和跟踪;肌肉厚度的计算。实验采集了肱二头肌的超声图像
以手工测量的方式验证了方法的有效性。实验结果表明:可以实现超声图像序列中肌肉厚度的自动测量。
Ultrasonography has the characteristic of noninvasive
radiation-free
real-time and so on. It has unparalleled advantages in the study of muscle contraction and relaxation process. Ultrasonic images can be used to obtain tissue data in real-time
from which physiological anatomical information such as muscle fiber angle
muscle fiber length
muscle cross-sectional area and muscle thickness can be extracted. Based on this
a method for measuring the thickness of biceps brachii is proposed. The method includes three steps: extraction and tracking of the superior sarcolemma feature point; extraction and tracking of the feature line of the inferior sarcolemma; and calculation of muscle thickness. Effectiveness of this method is verified by manual measurement on the collected images. Experimental results show that this method can achieve auto measurement of muscle thickness in sequence of ultrasound images.
基于表面肌电的运动意图识别方法研究及应用综述 [J]. 丁其川,熊安斌,赵新刚,韩建达. 自动化学报 . 2016(01)
基于sEMG信号的外骨骼式机器人上肢康复系统研究 [D]. 李庆玲. 哈尔滨工业大学 2009
超声序列图像中肌肉形态特征的自动测量方法研究 [D]. 凌姗. 中南大学 2014
基于肌动图(MMG)与肌电图(EMG)信号的假肢控制系统研究 [D]. 游淼. 中南大学 2011
Assessment of muscle fatigue using sonomyography: Muscle thickness change detected from ultrasound images [J] . J. Shi,Y.P. Zheng,X. Chen,Q.H. Huang. Medical Engineering and Physics . 2006 (4)
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