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A multi-task learning convolutional neural network for object pose estimation

A multi-task learning convolutional neural network for objec...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Wang, Yurui Jin, Shaokun Ou, Yongsheng Shenzhen Institutes of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Beijing China University of Chinese Academy of Sciences Beijing China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

ISBN: (纸本)9781728163215

Estimating 6D poses of objects from RGB images is very crucial for robots to interact with the surrounding environment and to cooperate with humans. It is a challenging problem due to the various shapes of objects, the occlusions among objects, as well as the complexity of the scene. In this study, we present a new multi-task convolutional neural network for 6D object pose estimation, which also learns the object region in the image to further improve the estimation result. A weighted loss computed from the training samples is adopted to guarantee that the components of the estimated pose are equally accurate. Additionally, we sythesize new virtual data based on the existing training data so as to overcome the possible adverse situation caused by insufficiency of training data. Experiments on the YCB-video dataset are undertaken to validate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Semantic Segmentation

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A Novel Gesture Recognition Technique based on sEMG Armband and Leap Motion Controller

A Novel Gesture Recognition Technique based on sEMG Armband ...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Zhang, Huanqing Xie, Jun Xiao, Yi Yang, Yuzhe Ren, Zhiyuan Zhang, Ruiwen Dong, Yuanzhe Tang, Xi Li, Guanglin Fang, Peng School of Mechanical Engineering Xi'An Jiaotong University Xi'an710049 China China Astronauts Research and Training Center National Key Laboratory of Human Factors Engineering Beijing100094 China Shenzhen Institute of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Engineering Laboratory of Neural Rehabilitation Technology Shenzhen518055 China

ISBN: (纸本)9781665481090

With the rapid development of human-computer interaction technology, it has become very common to use various sensors for gesture recognition to control machines or to complete specified tasks. This study proposes a fusion method that uses Leap Motion for gesture recognition and gForcePro+ to evaluate actual force of hands. A three-dimensional (3-D) virtual gesture recognition platform was designed in Unity. Leap Motion was used to control gestures in the virtual environment, and surface electromyography (sEMG) data was used to distinguish different forces of the same gesture. The success of grasping objects was judged by detecting and analyzing the sEMG signals and Leap Motion signals, combined with the size of the grasping objects. Experimental results showed that Leap Motion and gForcePro+ can be used together to control hand motion. In addition, the proposed system can be used to distinguish the same gesture with different force sizes, which can reflect different forces when the hand grasp objects with the same action. It was proved that the fusion technique of gesture recognition system based on Leap Motion and sEMG is effective for online gesture recognition. © 2022 IEEE.

关键词： Gesture recognition

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Attention mechanism-based monocular depth estimation and visual odometry

Attention mechanism-based monocular depth estimation and vis...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Zhang, Qieshi Lin, Dian Ren, Ziliang Kang, Yuhang Wu, Fuxiang Cheng, Jun Shenzhen Institute of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Guangdong Shenzhen China Chinese University of Hong Kong Hong Kong Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan University of Technology Hubei Wuhan China

ISBN: (纸本)9781665436786

In recent years, visual-inertial simultaneous localization and mapping (SLAM) have been widely researched and used. The monocular vision-based depth estimation and visual odometry (VO) plays a significant role in the SLAM system because of its low cost and high efficiency, which can be used to analyze the indoor environment for intelligent move robot application. Existing methods generally aim at the difference in pixel contrast between the previous and later frames to obtain the environment structure and camera pose. But the indifferent attention to the overall image makes the network spend extra computing power and hard to obtain the ideal results. For overcoming these disadvantages, an attention mechanism is proposed on basis of the original network and modified some convolution methods to make the network pay more attention to the key areas in the image and improve the accuracy of the estimation. The proposed approach is evaluated on the KITTI dataset, compared with the state-of-the-art methods achieves better results. © 2021 IEEE.

关键词： Vision

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Performance Evaluation of Head-Mounted Display based Brain-Computer Interface for Virtual Robotic Arm Operation

Performance Evaluation of Head-Mounted Display based Brain-C...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Yang, Yuzhe Xie, Jun Xiao, Yi Ren, Zhiyuan Zhang, Huanqing Xiao, Xianzi Dong, Yuanzhe Tang, Xi Li, Guanglin Fang, Peng Xi'An Jiaotong University School of Mechanical Engineering Xi'an710049 China China Astronauts Research and Training Center National Key Laboratory of Human Factors Engineering Beijing100094 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems The Shenzhen Engineering Laboratory of Neural Rehabilitation Technology Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781665481090

The steady-state visual evoked potential based brain-computer interface (SSVEP BCI) mostly uses desktop display to present the visual stimulation, and it cannot meet the needs of immersive brain-computer interaction. This study proposed the head-mounted display (HMD) implementation of the SSVEP BCI. And based on the head-mounted virtual reality (VR) glasses device, this study established the BCI system in the VR environment for the operation of the virtual robotic arm. In offline experiments, the system accuracy was 86.66% and the information transfer rate (ITR) was 18.33 bits/min. And in the online experiment, the recognition accuracy was 88.08% and the ITR was 19.26 bits/min. Experimental results verified the effectiveness of the proposed HMD based BCI system in the operation of the virtual robotic arm. © 2022 IEEE.

关键词： Brain computer interface

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Spasticity assessment with muscle coactivation of elbow flexors during passive stretch in Post-stroke Hemiplegia

Spasticity assessment with muscle coactivation of elbow flex...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Hui Wang Yanjuan Geng Peng Fang Guanglin Li CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China

the assessment of muscle properties is an essential prerequisite in the treatment of post-stroke muscle spasticity. Previous studies have shown that muscle coactivation, which reflects the simultaneous activation of agonist and antagonist muscle groups, is associated with muscle spasticity during voluntary contraction. However, current spasticity assessment approaches do not often consider muscle coactivation for passive contraction measured with surface electromyography (sEMG). The purpose here is to evaluate the validity and reliability of muscle co-activation based on sEMG for assessing spasticity of post-stroke patients. This study was conducted on 39 chronic hemiplegia post-stroke patients with varying degrees of elbow flexor spasticity. The severity of spasticity was assessed with Modified Ashworth Scale (MAS). The patients produced elbow flexion passively on affected arm. Two-channel surface sEMG recordings were acquired simultaneously for the biceps and triceps muscles. The effectiveness and reliability of the EMG-based spasticity assessment method were evaluated using Spearman's correlation analysis and intra class correlation coefficients (ICCs). The results showed that there was a statistically significant positive relationship between the level of activity and the coactivation index (R=0.710, P=0.003), while the ICCs for intra trial measures ranged between 0.928 and 0.976. Muscle coactivation is a promising tool for continuously quantifying muscle spasticity in post-stroke patients, suggesting that the EMG-based muscle coactivation index could be useful for assessing motor function.

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Two frequencies sequential coding for the assr-based brain-computer interface application

Two frequencies sequential coding for the assr-based brain-c...

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2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019

作者： Cao, Guozhi Xie, Jun Xu, Guanghua Fang, Peng Du, Guangjing Li, Min Zhang, Qing Li, Guanglin State Key Laboratory for Manufacturing Systems Engineering School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen Engineering Laboratory of Neural Rehabilitation Technology Shenzhen518055 China

ISBN: (纸本)9781728137261

Auditory steady state response (ASSR) based brain-computer interface (BCI) shows unique advantages compared with other BCIs such as steady-state visual evoked potentials (SSVEP) based BCI paradigm due to its visual-independent characteristic, and has attracted much attention from researchers. In this paper, a novel ASSR-based BCI using multiple frequencies sequential coding was proposed with the aim of improving the performance of conventional ASSR BCI. Each audio stimulus stream was modulated by two sequential frequencies, i.e., 4Hz and 13Hz for left ear stimulation and 5Hz and 9Hz for right ear stimulation. An experiment consisting of 200-trial offline task and 50-trial online task was performed for each subject and four subjects were recruited to participate in this study. Canonical correlation analysis (CCA) method was used in offline task to extract the ASSR response features, with which LDA model was trained. By applying the trained model to online task, we found that the accuracy of the proposed multiple frequencies sequential coding method is higher than that using the single frequency. And we also draw such a conclusion that the low frequency range can be used in ASSR-based BCIs. All of the results proved the feasibility of the proposed method to provide a new possible paradigm for practical ASSR BCI applications. © 2018 IEEE.

关键词： Brain computer interface

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Mid-air gestures for multi-fingered virtual assembly system with leap motion

Mid-air gestures for multi-fingered virtual assembly system ...

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2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019

作者： Du, Guangjing Xie, Jun Fang, Peng Xu, Guanghua Li, Min Li, Guanglin State Key Laboratory for Manufacturing Systems Engineering School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology & Shenzhen Engineering Laboratory of Neural Rehabilitation Technology Shenzhen518055 China

ISBN: (纸本)9781728137261

With the development of human-computer interaction and virtual reality technology, virtual assembly shows its advantages in the fields of robotic and mechanical assembly. However, the traditional virtual assembly is based on the mouse and keyboard devices to interact with the virtual environment with low interactivity and poor sense of reality. This paper proposed a novel approach for designing and implementing a virtual assembly training system based on multi-fingered mid-air gestures with Leap Motion controller. The procedures included the construction of assembly scene, the functional identification of the mid-air gestures and the design of the assembly process. This framework is validated through a sample assembly process of a single-stage gear reducer. Experimental results indicated that the system works well to implement assembly operations with immersive experience and high gesture recognition accuracy. From the results, it can be seen that the proposed system has the potential to be a useful tool for mechanical assembly education and industrial design and manufacturing. © 2018 IEEE

关键词： Product design

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Comparison of Blood Pressure Modulation by Low-Intensity Focused Ultrasound Stimulation of Carotid Sinus, Nodose Ganglion, and Vagus Nerve 46

Comparison of Blood Pressure Modulation by Low-Intensity Foc...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Wei, Jingjing Ji, Ning Wang, Lin Wu, Xinyu Li, Guanglin Lin, Wan-Hua Chinese Academy of Sciences Cas Key Lab of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shandong Zhongke Advanced Technology CO. LTD. Jinan250000 China

ISBN: (纸本)9798350371499

Low-intensity focused ultrasound stimulation (FUS) of the vagus nerve has proven effective in lowering blood pressure (BP) in our pilot animal study, opening new possibilities for noninvasive physiotherapy for hypertension. To further explore the impact of BP regulation by FUS on other targets, we compared the BP modulation pattern when applying FUS to the left carotid sinus, nodose ganglion, and vagus nerve trunk, respectively. FUS with different acoustic intensities was applied to each target, while continuous BP waveforms were synchronously recorded in the right common carotid artery. Subsequently, systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were extracted and analyzed before, during, and after FUS. The results revealed that FUS targeting the carotid sinus and nodose ganglion could also induce reductions in BP. However, both the degree of BP reduction and the sustained duration were less than those achieved with vagus nerve stimulation. Moreover, the ultrasound stimulation intensity threshold for inducing a hypotensive effect is lower when stimulating the vagus nerve compared to stimulating the carotid sinus and nodose ganglion. This study provides compelling evidence supporting the selection of the vagus nerve as the appropriate target for FUS in regulating BP. © 2024 IEEE.

关键词： Blood pressure

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How do we perceive emotion from a 3-D virtual talking head: Evidence from functional near-infrared spectroscopy 13

How do we perceive emotion from a 3-D virtual talking head: ...

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13th International Conference on Interfaces and human Computer Interaction 2019, IHCI 2019, 12th International Conference on Game and Entertainment Technologies 2019, GET 2019 and 13th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2019, CGVCVIP 2019

作者： Wang, Jianying Chen, Jiangtao Yan, Nan Wang, Lan Ng, Lawrence CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences University Town of Shenzhen 1068 Xueyuan Boulevard Xili Nanshan Shenzhen518055 China Speech Science Laboratory University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9789898533913

Emotional interaction plays an important role in human-computer interaction. Although more and more virtual heads are endowed with a series of facial expressions under the conversational scenarios, the similarities and differences in neural mechanism underlying emotional perception between virtual head and human are still largely unknown. In the present study, we investigated the activation of emotional perception activities in the dorsolateral prefrontal cortex (DLPFC) region associated with when humans when beings perceiving emotions from 3-D virtual talking heads by using functional near-infrared spectroscopy (fNIRS). Three dynamic emotional stimuli were consisting of 3-D virtual talking head and human face with mute mode or voice presented by twenty participants. The behavioral results showed that participants had lower accuracy watching mute 3-D virtual talking head videos (3DMute) than watching human face videos with voice (HFMute) especially for in anger and happiness stimuli except for neutral emotion. The fNIRS results observed that there was no difference in DLPFC activity area for the observation of 3-D virtual talking head and human face. However, it was found that a stronger DLPFC region had stronger activation was observed for 3-D virtual talking head videos with voice (3DVoice) than 3DMute. In addition, the a stronger activation in DLPFC activation region for affectively angry emotion was videos observed in females was demonstrated, but yet there was no gender difference was found in gender during watching both types for happiness videos. The present results work provided preliminary evidence in physiology mechanism in human-computer interaction. © Copyright 2019 IADIS Press. All rights reserved.

关键词： human computer interaction

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Design of A Prosthetic Hand for Multiple hand Motions*

Design of A Prosthetic Hand for Multiple hand Motions*

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IEEE International Conference on Robotics and Biomimetics

作者： Xiaobei Jing Xu Yong Guanglin Li Jiang Jiang Hiroshi Yokoi CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences (CAS) Department of Mechanical Engineering and Intelligent Systems The University of Electro-communications

In this paper, a prosthetic hand which has been considered both of multiple hand motions and lightweight was presented. By integrating different digits functions of stable linkage four fingers and adaptive thumb, the proposed hand is capable to realize 10 types of hand motions based on the frequently-used hand motions. Furthermore, the proposed hand is modeled based on an adult hand size, with three motors embedded in the palm. Finally, the experiment had been conducted to verify the motion function and grasp performance.

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