| 1. |
- Deng, Min, et al.
(författare)
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Genome-wide association analyses in Han Chinese identify two new susceptibility loci for amyotrophic lateral sclerosis
- 2013
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 45:6, s. 697-
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Tidskriftsartikel (refereegranskat)abstract
- To identify susceptibility genes for amyotrophic lateral sclerosis (ALS), we conducted a genome-wide association study (GWAS) in 506 individuals with sporadic ALS and 1,859 controls of Han Chinese ancestry. Ninety top SNPs suggested by the current GWAS and 6 SNPs identified by previous GWAS were analyzed in an independent cohort of 706 individuals with ALS and 1,777 controls of Han Chinese ancestry. We discovered two new susceptibility loci for ALS at 1q32 (CAMK1G, rs6703183, P-combined = 2.92 x 10(-8), odds ratio (OR) = 1.31) and 22p11 (CABIN1 and SUSD2, rs8141797, P-combined = 2.35 x 10(-9), OR = 1.52). These two loci explain 12.48% of the overall variance in disease risk in the Han Chinese population. We found no association evidence for the previously reported loci in the Han Chinese population, suggesting genetic heterogeneity of disease susceptibility for ALS between ancestry groups. Our study identifies two new susceptibility loci and suggests new pathogenic mechanisms of ALS.
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| 2. |
- Gbouna, Zakka Vincent, et al.
(författare)
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User-Interactive Robot Skin With Large-Area Scalability for Safer and Natural Human-Robot Collaboration in Future Telehealthcare
- 2021
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Ingår i: IEEE journal of biomedical and health informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-2194 .- 2168-2208. ; 25:12, s. 4276-4288
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Tidskriftsartikel (refereegranskat)abstract
- With the fourth revolution of healthcare, i.e., Healthcare 4.0, collaborative robotics is spilling out from traditional manufacturing and will blend into human living or working environments to deliver care services, especially telehealthcare. Because of the frequent and seamless interaction between robots and care recipients, it poses several challenges that require careful consideration: 1) the ability of the human to collaborate with the robots in a natural manner; and 2) the safety of the human collaborating with the robot. In this regard, we have proposed a proximity sensing solution based on the self-capacitive technology to provide an extended sense of touch for collaborative robots, allowing approach and contact measurement to enhance safe and natural human-robot collaboration. The modular design of our solution enables it to scale up to form a large-area sensing system. The sensing solution is proposed to work in two operation modes: the interaction mode and the safety mode. In the interaction mode, utilizing the ability of the sensor to localize the point of action, gesture command is used for robot manipulation. In the safety mode, the sensor enables the robot to actively avoid obstacles.
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| 3. |
- Kong, Depeng, et al.
(författare)
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Bioinspired Co-Design of Tactile Sensor and Deep Learning Algorithm for Human-Robot Interaction
- 2022
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Ingår i: ADVANCED INTELLIGENT SYSTEMS. - : Wiley. - 2640-4567. ; 4:6
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Tidskriftsartikel (refereegranskat)abstract
- Robots equipped with bionic skins for enhancing the robot perception capability are increasingly deployed in wide applications ranging from healthcare to industry. Artificial intelligence algorithms that can provide bionic skins with efficient signal processing functions further accelerate the development of this trend. Inspired by the somatosensory processing hierarchy of humans, the bioinspired co-design of a tactile sensor and a deep learning-based algorithm is proposed herein, simplifying the sensor structure while providing computation-enhanced tactile sensing performance. The soft piezoresistive sensor, based on the carbon black-coated polyurethane sponge, offers a continuous sensing area. By utilizing a customized deep neural network (DNN), it can detect external tactile stimulus spatially continuously. Besides, a novel data augmentation method is developed based on the sensor's hexagonal structure that has a sixfold rotation symmetry. It can significantly enhance the generalization ability of the DNN model by enriching the collected training data with generated pseudo-data. The functionality of the sensor and the robustness of the proposed data augmentation strategy are verified by precisely recognizing five touch modalities, illustrating a well-generalized performance, and providing a promising application prospect in human-robot interaction.
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| 4. |
- Lv, Honghao, et al.
(författare)
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Impacts of Wireless on Robot Control : The Network Hardware-in-the-Loop Simulation Framework and Real-Life Comparisons
- 2023
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 19:9, s. 9255-9265
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Tidskriftsartikel (refereegranskat)abstract
- As many robot applications become more reliant on wireless communications, wireless network latency and reliability have a growing impact on robot control. This article proposes a network hardware-in-the-loop (N-HiL) simulation framework to evaluate the impacts of wireless on robot control more efficiently and accurately, and then improve the design by employing correlation analysis between communication and control performances. The N-HiL method provides communication and robot developers with more trustworthy network conditions, while the huge efforts and costs of building and testing the entire physical robot system in real life are eliminated. These benefits are showcased in two representative latency-sensitive applications: 1) safe multirobot coordination for mobile robots, and 2) human-motion-based teleoperation for manipulators. Moreover, we deliver a preliminary assessment of two new-generation wireless technologies, the Wi-Fi6 and 5G, for those applications, which has demonstrated the effectiveness of the N-HiL method as well as the attractiveness of the wireless technologies.
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| 5. |
- Lv, Honghao, et al.
(författare)
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Towards Intercontinental Teleoperation : A Cloud-Based Framework for Ultra-Remote Human-Robot Dual-Arm Motion Mapping
- 2023
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Ingår i: Intelligent Robotics and Applications. - : Springer Nature. ; , s. 132-144
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Konferensbidrag (refereegranskat)abstract
- Teleoperated robots offer a unique combination of robotic strength and precision, coupled with human judgment and ingenuity, to enhance productivity and safety in complex, unstructured, and hazardous industrial environments. However, teleoperation over ultra-remote distances has posed a significant challenge, with control performance being compromised by the inherent trade-off between distance and latency. This study presents a novel cloud-based human-robot motion mapping framework for ultra-remote teleoperation. An intuitive dual-arm human-robot motion mapping framework based on capturing human motion has been implemented, and private network connectivity is established using the Google Cloud platform for the efficient transfer of control data required for human-robot motion mapping. Moreover, a novel feedforward control framework is proposed to mitigate the negative impact of high network latency on teleoperation control performance. To demonstrate the feasibility of the proposed approach, an intercontinental teleoperation system between China and Sweden was developed, and a series of practical applications were demonstrated by capturing the motion of an operator in Sweden to control the dual-arm robot located over 7800 km away in China. The proposed feedforward control framework for intercontinental teleoperation has the potential utility for improving human-robot interaction performance in ultra-remote teleoperation scenarios with high network latency. More demonstration videos can be found at https://fsie-robotics.com/intercontinental-teleoperation/.
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