المؤلفون: Wang, Xin, Song, Qiuzhi, Zhou, Shitong, Tang, Jing, Chen, Kezhong, Cao, Heng

المساهمون: The National key R&D Program of China“The study on Load-bearing and Moving Support Exoskeleton Robot Key Technology and Typical Application

المصدر: International Journal of Advanced Robotic Systems ; volume 16, issue 4, page 172988141986318 ; ISSN 1729-8814 1729-8814

مصطلحات موضوعية: Artificial Intelligence, Computer Science Applications, Software

الوصف: In this article, a method of multi-connection load compensation and load information calculation for an upper-limb exoskeleton is proposed based on a six-axis force/torque sensor installed between the exoskeleton and the end effector. The proposed load compensation method uses a mounted sensor to measure the force and torque between the exoskeleton and load of different connections and adds a compensator to the controller to compensate the component caused by the load in the human–robot interaction force, so that the human–robot interaction force is only used to operate the exoskeleton. Therefore, the operator can manipulate the exoskeleton with the same interaction force to lift loads of different weights with a passive or fixed connection, and the human–robot interaction force is minimized. Moreover, the proposed load information calculation method can calculate the weight of the load and the position of its center of gravity relative to the exoskeleton and end effector accurately, which is necessary for acquiring the upper-limb exoskeleton center of gravity and stability control of whole-body exoskeleton. In order to verify the effectiveness of the proposed method, we performed load handling and operational stability experiments. The experimental results showed that the proposed method realized the expected function.

الإتاحة: https://doi.org/10.1177/1729881419863186Test

المؤلفون: Zhu, Jun, Wang, Yu, Jiang, Jinlin, Sun, Bo, Cao, Heng

المصدر: International Journal of Advanced Robotic Systems ; volume 14, issue 1, page 172988141668695 ; ISSN 1729-8814 1729-8814

مصطلحات موضوعية: Artificial Intelligence, Computer Science Applications, Software

الوصف: This article presents the design and experimental testing of a unidirectional variable stiffness hydraulic actuator for load-carrying knee exoskeleton. The proposed actuator is designed for mimicking the high-efficiency passive behavior of biological knee and providing actively assistance in locomotion. The adjustable passive compliance of exoskeletal knee is achieved through a variable ratio lever mechanism with linear elastic element. A compact customized electrohydraulic system is also designed to accommodate application demands. Preliminary experimental results show the prototype has good performances in terms of stiffness regulation and joint torque control. The actuator is also implemented in an exoskeleton knee joint, resulting in anticipant human-like passive compliance behavior.

الإتاحة: https://doi.org/10.1177/1729881416686955Test

المؤلفون: Dong Ni, Wufeng Xue, Cao Heng, Yiqin Cao, Shuo Li, Hongrong Wei, Yongjin Zhou

المصدر: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597122
MICCAI (2)

مصطلحات موضوعية: Sequence, Computer science, business.industry, Consistency (statistics), Pattern recognition, Segmentation, Artificial intelligence, Tracking (particle physics), business

الوصف: Accurate and temporal-consistent segmentation of echocardiography is important for diagnosing cardiovascular disease. Existing methods often ignore consistency among the segmentation sequences, leading to poor ejection fraction (EF) estimation. In this paper, we propose to enhance temporal consistency of the segmentation sequences with two co-learning strategies of segmentation and tracking from ultrasonic cardiac sequences where only end diastole and end systole frames are labeled. First, we design an appearance-level co-learning (CLA) strategy to make the segmentation and tracking benefit each other and provide an eligible estimation of cardiac shapes and motion fields. Second, we design another shape-level co-learning (CLS) strategy to further improve segmentation with pseudo labels propagated from the labeled frames and to enforce the temporal consistency by shape tracking across the whole sequence. Experimental results on the largest publicly-available echocardiographic dataset (CAMUS) show the proposed method, denoted as CLAS, outperforms existing methods for segmentation and EF estimation. In particular, CLAS can give segmentations of the whole sequences with high temporal consistency, thus achieves excellent estimation of EF, with Pearson correlation coefficient 0.926 and bias of 0.1%, which is even better than the intra-observer agreement.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::c7c81d793b8a73060f4af0d7e6dccc5eTest
https://doi.org/10.1007/978-3-030-59713-9_60Test

المؤلفون: Yuan Yan Tang, Wang Yiding, Jiang Xiaochen, Cao Heng

المصدر: Sensors (Basel, Switzerland)
Sensors
Volume 19
Issue 17
Sensors, Vol 19, Iss 17, p 3718 (2019)

مصطلحات موضوعية: Brightness, Computer science, dorsal hand vein recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-invariant feature transform, 02 engineering and technology, lcsh:Chemical technology, Biochemistry, Vein recognition, Article, Analytical Chemistry, Pattern Recognition, Automated, Veins, 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Image Processing, Computer-Assisted, Humans, lcsh:TP1-1185, Computer vision, 030216 legal & forensic medicine, Electrical and Electronic Engineering, mutual information, Instrumentation, block, business.industry, Mutual information, bit planes, Hand, Atomic and Molecular Physics, and Optics, cross-device, Dorsal hand, 020201 artificial intelligence & image processing, Artificial intelligence, business, Algorithms, Bit plane

الوصف: The dorsal hand vein images captured by cross-device may have great differences in brightness, displacement, rotation angle and size. These deviations must influence greatly the results of dorsal hand vein recognition. To solve these problems, the method of dorsal hand vein recognition was put forward based on bit plane and block mutual information in this paper. Firstly, the input gray image of dorsal hand vein was converted to eight-bit planes to overcome the interference of brightness inside the higher bit planes and the interference of noise inside the lower bit planes. Secondly, the texture of each bit plane of dorsal hand vein was described by a block method and the mutual information between blocks was calculated as texture features by three kinds of modes to solve the problem of rotation and size. Finally, the experiments cross-device were carried out. One device was used to be registered, the other was used to recognize. Compared with the SIFT (Scale-invariant feature transform, SIFT) algorithm, the new algorithm can increase the recognition rate of dorsal hand vein from 86.60% to 93.33%.

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dbb51a6f7b364119b8c0d6a28e7d2382Test
http://europepmc.org/articles/PMC6749406Test

المؤلفون: He Xi, Cui Wanlong, Yang Shubin, Cao Heng

المصدر: Journal of Convergence Information Technology. 6:251-256

مصطلحات موضوعية: Computer Networks and Communications, Computer science, business.industry, Color normalization, Balanced histogram thresholding, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Histogram matching, Hardware and Architecture, Computer Science::Computer Vision and Pattern Recognition, Histogram, Night vision, Median filter, Computer vision, Artificial intelligence, business, Algorithm, Histogram equalization, Image histogram

الوصف: In allusion to characteristics of low contrast, weak-arrangement gray and dim vision in low-lightlevel night vision image, double-plateaus histogram enhancement algorithm is presented. Firstly, median filter is processed on original image histogram to delete those zero-gray values. By selfadaptive setting double-plateaus thresholds as the upper and lower limit for the processed histogram, the algorithm can enhance the image efficiently. By setting a higher threshold, the algorithm can constrain the background and noises. At the same time, it can magnify dim targets and image details by setting a lower threshold. With the proposed algorithm, disadvantages of classical histogram and other plateaus histogram enhancement algorithm are overcome while achieving high contrast. Experiments prove that the proposed algorithm can enhance image contrast effectively and preserve image details simultaneously. Moreover, it can also overcome over-bright phenomenon. It is an effective enhancement algorithm for low-light-level night vision image.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::12f965ad442351975c83400c679197fcTest
https://doi.org/10.4156/jcit.vol6.issue1.29Test

المؤلفون: Yu Xianchuan, Hu Dan, Cao Heng-zhi, Chu Xiao-feng

المصدر: GIScience & Remote Sensing. 48:130-140

مصطلحات موضوعية: Synthetic aperture radar, Pixel, business.industry, Land cover, Quantitative Biology::Other, Single pixel, Computer Science::Graphics, Geography, Computer Science::Computer Vision and Pattern Recognition, Decomposition (computer science), General Earth and Planetary Sciences, Computer vision, Artificial intelligence, business, Physics::Atmospheric and Oceanic Physics, Remote sensing

الوصف: In the decomposition of synthetic aperture radar (SAR) images with mixed pixels, two issues cannot be avoided; (1) there are more land cover types than the number of SAR image channels; and (2) the...

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::4ec3797e2e69b1c2dec8d7ff8c12dc3bTest
https://doi.org/10.2747/1548-1603.48.1.130Test