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脉搏波是分析人体心血管系统生理状况的重要检测对象,可穿戴光电设备采集的脉搏信号常因人体运动而引入运动伪影,进而影响脉率检测结果的准确性,由于伪影的主要频率分量和光电信号频率相重叠,所以减少伪影有难度。针对现有脉率检测精度不高、抗运动干扰能力不足问题,提出一种结合非线性自适应滤波和线性调频Z变换(CZT)的脉率检测方法。首先对光电容积脉搏波描记法(PPG)采集的信号预处理滤除高频干扰和基线漂移,然后选用微机电系统(MEMS)检测加速度信号作为参考信号,构建基于最小均方(LMS)的非线性自适应滤波器去除运动伪影,最后利用线性调频Z变换(CZT)对信号进行频谱分析计算脉率值。实验通过对10名受试者采集的实验数据进行性能评估,结果表明,该方法能有效从干扰脉搏波信号中恢复出原始信号,测得的受试者脉率平均绝对误差为196 bpm,具有较高的准确率和抗干扰能力。 相似文献
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基于结构保持的MR图像运动伪影快速抑制方法 总被引:1,自引:0,他引:1
目前核磁共振图像运动伪影的校正方法普遍是基于K空间数据的方法,本文提出一种直接对核磁共振图像进行伪影校正的后处理方法.基于非局部均值总变差去噪的思想设计构造了结构保持的运动伪影校正模型,该模型由非局部均值正则项和块相似保真项构成,正则项可以有效去除运动伪影和噪声的同时保持图像的结构;将各向异性结构张量作为块相似保真项中的权函数,实现在不同区域有不同的扩散方式,在去除图像运动伪影的同时保留图像的细节信息.模型的数值求解采用分裂Bregman方法实现.本文提出的方法充分考虑了图像的几何结构特性,实验结果表明,该方法能有效去除运动伪影并保留有价值的图像细节信息,同时提高了运算速度. 相似文献
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本文作者提出一种基于图像最大互信息量熵差分割的CT金属伪影消除算法.新算法首先利用各向异性高斯滤波对原始CT图像进行预处理,以抑制CT图像中的部分噪声和伪影;其后配合最大互信息量熵差分割算法,对预处理CT图像进行自适应多目标分割;接着通过对分割后的金属物图像及由金属引起的伪影进行正向投影,得到金属物的投影数据,并将此投影数据与原始CT图像的正向投影数据做"与"运算,以获取金属物投影在投影空间内的索引函数,再将原始CT投影数据减除金属物对应的投影数据部分,利用索引函数完成原始CT投影数据中的反馈式插值处理,得到修正的投影数据;最后对修正的投影数据采用滤波反投影完成CT图像重建.实验表明,本文算法对含有金属伪影的真实体模CT图像和临床CT图像的伪影消除均有尚佳表现. 相似文献
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针对连续回撤导管采集的、覆盖多个心动周期的冠状动脉内超声(ICUS)图像序列中存在的运动伪影问题,采用图像分析技术,对ICUS图像序列进行离线门控,从而改善ICUS纵向视图的视觉效果。首先,通过逐帧比较ICUS图像的灰度特征,构造ICUS序列的差异矩阵;然后,从差异矩阵中搜索出具有最小累计差异值的路径,为各帧找到其在相邻心动周期中的对应帧;最后,在滤波后的差异矩阵中,沿最优路径找到表示在各相邻心动周期舒张末期采集的图像对的点,得到最终的门控序列。对临床采集ICUS序列的实验验证了方法的可行性和精度。 相似文献
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提出一种光栅X射线相衬断层扫描中吸收信号环形伪影的去除方法。该方法采用正弦图域和重建图域结合的处理算法。对于弱伪影,通过正弦图域的排序和滤波去除。而对于强伪影,首先根据环形伪影在极坐标系的表现,计算残差图像,转换到笛卡尔坐标系得到伪影像素和样品的边界;进而使用基于机器学习的图像分割方法获取每一类样品的分布,同时为了保护边界信息,通过形态学操作获得样本的内部区域;最后再利用残差图像的分布特征定位伪影像素,并使用临近非伪影像素均值替代。实验结果表明该方法可以在不破坏样品边界的前提下有效地去除图像中的环形伪影。 相似文献
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金属伪影严重地影响CT图像的质量及其医学诊断价值。考虑到临床数据的可靠性及时效性,正弦图修复及其改进的方法已成为近年来研究的热点。典型的NMAR方法(Normalized Metal Artifact Reduction),多数情况下能准确地恢复原始数据,并尽可能少地残留或引入新的伪影。然而当出现高密度组织(骨头等)与金属不相邻时,就会在金属与高密度组织间不可避免地引入或残留部分伪影。本文在NMAR算法的基础上,引入了一种基于正弦图中轨迹修复的金属伪影去除方法(TNMAR)。具体地,在NMAR方法中正弦图归一化后的区域修复期间,引入了高密度组织轨迹方向的平滑修复。此方法一定程度上削减了NMAR修复后金属与高密度组织间的残留伪影,且尽可能地恢复了原图的高对比度及组织细节。临床中,有很高的应用价值。 相似文献
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Shan Wang Yuanlai Fang Hao He Lei Zhang Chang'an Li Jianyong Ouyang 《Advanced functional materials》2021,31(5):2007495
Wearable stretchable strain sensors can have important applications in many areas. However, the high noise is a big hurdle for their application to monitor body movement. The noise is mainly due to the motion artifacts related to the poor contact between the sensors and skin. Here, wearable stretchable dry and self-adhesive strain sensors that can always form conformal contact to skin even during body movement are demonstrated. They are prepared via solution coating and consist of two layers, a dry adhesive layer made of biocompatible elastomeric waterborne polyurethane and a sensing layer made of a non-adhesive composite of reduced graphene oxide and carbon nanotubes. The adhesive layer makes the sensors conformal to skin, while the sensing layer exhibits a resistance sensitive to strain. The sensors are used to accurately monitor both small- and large-scale body movements, including various joint movements and muscle movements. They can always generate high-quality signals even on curvilinear skin surface and during irregular skin deformation. The sensitivity is remarkably higher while the noise is saliently lower than the non-adhesive strain sensors. They can also be used to monitor the movements along two perpendicular directions, which cannot be achieved by the non-adhesive strain sensors. 相似文献
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Yan Wang Li Wang Tingting Yang Xiao Li Xiaobei Zang Miao Zhu Kunlin Wang Dehai Wu Hongwei Zhu 《Advanced functional materials》2014,24(29):4666-4670
Sensing strain of soft materials in small scale has attracted increasing attention. In this work, graphene woven fabrics (GWFs) are explored for highly sensitive sensing. A flexible and wearable strain sensor is assembled by adhering the GWFs on polymer and medical tape composite film. The sensor exhibits the following features: ultra‐light, relatively good sensitivity, high reversibility, superior physical robustness, easy fabrication, ease to follow human skin deformation, and so on. Some weak human motions are chosen to test the notable resistance change, including hand clenching, phonation, expression change, blink, breath, and pulse. Because of the distinctive features of high sensitivity and reversible extensibility, the GWFs based piezoresistive sensors have wide potential applications in fields of the displays, robotics, fatigue detection, body monitoring, and so forth. 相似文献
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针对隔行扫描到逐行扫描转换中出现的运动图像锯齿现象,提出适用于去锯齿的运动检测和基于角度提取的场内插值算法。利用相邻4场运动差值进行运动检测,并结合待插像素相邻行和隔行相关像素点的夹角进行加权平均,提取相关度大的角度点进行场内插值。实验结果表明,算法有效提高了峰值性噪比,也有效降低了均方差,实际图像去锯齿效果良好。 相似文献
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Nathan Rodeheaver Robert Herbert Yun-Soung Kim Musa Mahmood Hojoong Kim Jae-Woong Jeong Woon-Hong Yeo 《Advanced functional materials》2021,31(36):2104070
Recent developments of micro-sensors and flexible electronics allow for the manufacturing of health monitoring devices, including electrocardiogram (ECG) detection systems for inpatient monitoring and ambulatory health diagnosis, by mounting the device on the chest. Although some commercial devices in reported articles show examples of a portable recording of ECG, they lose valuable data due to significant motion artifacts. Here, a new class of strain-isolating materials, hybrid interfacial physics, and soft material packaging for a strain-isolated, wearable soft bioelectronic system (SIS) is reported. The fundamental mechanism of sensor-embedded strain isolation is defined through a combination of analytical and computational studies and validated by dynamic experiments. Comprehensive research of hard-soft material integration and isolation mechanics provides critical design features to minimize motion artifacts that can occur during both mild and excessive daily activities. A wireless, fully integrated SIS that incorporates a breathable, perforated membrane can measure real-time, continuous physiological data, including high-quality ECG, heart rate, respiratory rate, and activities. In vivo demonstration with multiple subjects and simultaneous comparison with commercial devices captures the SIS's outstanding performance, offering real-world, continuous monitoring of the critical physiological signals with no data loss over eight consecutive hours in daily life, even with exaggerated body movements. 相似文献
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呼吸、心率、鼾声反映了人体在睡眠时的大量信息,该文以聚偏氟乙烯(PVDF)作为敏感单元进行呼吸、脉搏、鼾声信号的监测。根据所采用的传感器特性分别进行了电荷放大电路、陷波电路及电压放大电路的设计。硬件电路通过聚合物锂电池进行供电,根据聚合物电池的特性分别为电池设计了充电电路、保护电路及放电电路,硬件电路整体集成在一块印制电路板(PCB)上。同时设计了基于Android 设备的APP,以可视化形式实时显示生理信号数据,并对其进行长期储存,便于后期医生进行睡眠呼吸病症的分析诊断。该研究的目的是能准确监测睡眠生理参数,提高被测试者的使用舒适感。 相似文献
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为了解决心电信号中R波的检测问题,研究验证一种结合自适应阈值的极大值搜索与数学形态学的R波检测算法。数学形态学算法是基于信号局部特征的,可以有效突出信号的峰谷点。考虑了心电信号特点的自适应阈值极大值搜索算法,可以敏感检测R波的准确位置。通过对MIT-BIH心率变异数据库中多组心电数据的仿真验证研究,实验结果表明,两种分析方法的结合可以有效消除心电信号的基线漂移或异常病态心率对检测的影响,能有效实现心电信号中R波的实时检测,预期本算法在心电信号的自动分析中将会扮演更为重要的角色。 相似文献