2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)最新文献_第6页

Development of a Soft Exosuit for Industriale Applications 工业用软外排衣的研制

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487907

Yongtae G. Kim, M. Xiloyannis, D. Accoto, L. Masia

{"title":"Development of a Soft Exosuit for Industriale Applications","authors":"Yongtae G. Kim, M. Xiloyannis, D. Accoto, L. Masia","doi":"10.1109/BIOROB.2018.8487907","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487907","url":null,"abstract":"Wearable robotic devices and exoskeletons, that assist human beings in physically-demanding tasks have the potential to both increase productivity and reduce the risk of musculoskeletal disorders. Soft exoskeletons, known as exosuit, provide improved portability and fit. While many exosuits are populating the market to support light weights, very few are powerful enough to reinforce workers in lifting heavy loads. Adopting the advantages of novel soft-robotic principles, we propose a voice-controlled upper limb exosuit designed to aid its user in lifting up to 10kg per arm. The exosuit uses a wire-driven mechanism to transmit power from a proximally-located actuation stage to the shoulder and elbow. Forces are transmitted to the human body via soft, textile-based components. We evaluate the impact of the device on the muscular effort of a wearer in both a lifting and a holding task. Holding a weight of 14kg with the exosuit results in an average reduction in muscular effort of the biceps brachii and anterior deltoid of 50% and 68%, respectively. Similarly, lifting a weight of 7kg with the exosuit reduces the muscular activity of the same two muscles by 23.4% and 41.2%, respectively.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115903670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Exploratory Evaluation of the Force Myography (FMG) Signals Usage for Admittance Control of a Linear Actuator 力肌图(FMG)信号用于线性驱动器导纳控制的探索性评价

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8488028

Maram Sakr, C. Menon

{"title":"Exploratory Evaluation of the Force Myography (FMG) Signals Usage for Admittance Control of a Linear Actuator","authors":"Maram Sakr, C. Menon","doi":"10.1109/BIOROB.2018.8488028","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8488028","url":null,"abstract":"Force Myography (FMG) is a technique involving the use of force sensors on the surface of the limb to detect the volumetric changes in the underlying musculotendinous complex. This paper investigates the feasibility of employing force-sensing resistors (FSRs) worn on the arm that measure the FMG signals for force prediction in dynamic conditions. The predicted force value can be mapped into velocity value to control a linear actuator to track hand movements. Two FMG bands were donned on the participant wrist and forearm muscle belly to measure the FMG signals during force exertion. An accurate force transducer was used for labeling the FM G signals by measuring the exerted force. Three regression algorithms including kernel ridge regression (KRR), support vector regression (SVR), and general regression neural network (G RNN), were used in this study for predicting hand force using the FMG signals. The data were collected for 200 seconds for training the regression model. Then, the trained model was used for online force prediction for 430 seconds. The testing accuracy was 0.92, 0.90 and 0.79, using KRR, SVR and GRNN, respectively. These results will be beneficial for monitoring hand force during human-robot interaction or controlling the robot movement.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"391 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115990438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Large-Stroke Varifocal Mirror with Hydraulic Actuation for Endoscopic Laser Surgery 内窥镜激光手术用液压驱动大行程变焦镜

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487927

A. Geraldes, A. Jacassi, P. Fiorini, L. Mattos

引用次数: 1

Learning to Reproduce Visually Similar Movements by Minimizing Event-Based Prediction Error 通过最小化基于事件的预测误差来学习再现视觉上相似的动作

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487959

Jacques Kaiser, Svenja Melbaum, J. C. V. Tieck, A. Rönnau, Martin Volker Butz, R. Dillmann

{"title":"Learning to Reproduce Visually Similar Movements by Minimizing Event-Based Prediction Error","authors":"Jacques Kaiser, Svenja Melbaum, J. C. V. Tieck, A. Rönnau, Martin Volker Butz, R. Dillmann","doi":"10.1109/BIOROB.2018.8487959","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487959","url":null,"abstract":"Prediction is believed to play an important role in the human brain. However, it is still unclear how predictions are used in the process of learning new movements. In this paper, we present a method to learn movements from visual prediction. The method consists of two phases: learning a visual prediction model for a given movement, then minimizing the visual prediction error. The visual prediction model is learned from a single demonstration of the movement where only visual input is sensed. Unlike previous work, we represent visual information with event streams as provided by a Dynamic Vision Sensor. This allows us to only process changes in the environment instead of complete snapshots using spiking neural networks. By minimizing the prediction error, movements visually similar to the demonstration are learned. We evaluate our method by learning simple movements from human demonstrations on different simulated robots. We show that the definition of the visual prediction error greatly impacts movements learned by our method.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"02 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127252262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Bioinspired Adaptive Spiking Neural Network to Control NAO Robot in a Pavlovian Conditioning Task 生物自适应脉冲神经网络控制NAO机器人的巴甫洛夫条件反射任务

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487202

A. Antonietti, C. Casellato, E. D’Angelo, A. Pedrocchi

{"title":"Bioinspired Adaptive Spiking Neural Network to Control NAO Robot in a Pavlovian Conditioning Task","authors":"A. Antonietti, C. Casellato, E. D’Angelo, A. Pedrocchi","doi":"10.1109/BIOROB.2018.8487202","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487202","url":null,"abstract":"Ahstract- The cerebellum has a central role in fine motor control and in various neural processes, as in associative paradigms. In this work, a bioinspired adaptive model, developed by means of a spiking neural network made of thousands of artificial neurons, has been leveraged to control a humanoid NAO robot in real-time. The learning properties of the system have been challenged in a classic cerebellum-driven paradigm, the Pavlovian timing association between two provided stimuli, here implemented as a laser-avoidance task. The neurophysiological principles used to develop the model, succeeded in driving an adaptive motor control protocol with acquisition and extinction phases. The spiking neural network model showed learning behaviors similar to the ones experimentally measured with human subjects in the same conditioning task. The model processed in real-time external inputs, encoded as spikes, and the generated spiking activity of its output neurons was decoded, in order to trigger the proper response with a correct timing. Three long-term plasticity rules have been embedded for different connections and with different time-scales. The plasticities shaped the firing activity of the output layer neurons of the network. In the Pavlovian protocol, the neurorobot successfully learned the correct timing association, generating appropriate responses. Therefore, the spiking cerebellar model was able to reproduce in the robotic platform how biological systems acquire and extinguish associative responses, dealing with noise and uncertainties of a real-world environment.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127816524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proposal of Non-rotating Joint Drive Type Mechanical Assist Device for Squat Lifting by Using Leaf and Compression Spring 叶片-压缩弹簧非旋转关节驱动式深蹲提升机械辅助装置的设计

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487627

Hirokazu Arakawa, Shun Mohri, Kazuya Yokoyama, Yasuyuki Yamada, Isao Kikutani, Taro Nakamura

引用次数: 0

The Inverted Muscle Skeleton Approach: Moving Beyond Rigid Exoskeletons 反向肌肉骨骼方法:超越刚性外骨骼

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487703

M. E. Grootens, E. Hekman, H. Kooij

引用次数: 0

Design and Development of Customized Physical Interfaces to Reduce Relative Motion Between the User and a Powered Ankle Foot Exoskeleton 定制物理接口的设计与开发，以减少用户与动力踝足外骨骼之间的相对运动

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487706

Kevin Langlois, Marta Moltedo, T. Baček, C. R. Guerrero, B. Vanderborght, D. Lefeber

引用次数: 20

Design and Control of a Novel Grip Amplifier to Support Pinch Grip with a Minimal Soft Hand Exoskeleton 一种支持捏握的新型握持放大器的设计与控制

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487918

Quentin Sanders, Shusuke Okita, J. Lobo-Prat, D. S. D. Lucena, Brendan W. Smith, D. Reinkensmeyer

{"title":"Design and Control of a Novel Grip Amplifier to Support Pinch Grip with a Minimal Soft Hand Exoskeleton","authors":"Quentin Sanders, Shusuke Okita, J. Lobo-Prat, D. S. D. Lucena, Brendan W. Smith, D. Reinkensmeyer","doi":"10.1109/BIOROB.2018.8487918","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487918","url":null,"abstract":"Hand exoskeletons could potentially improve hand use after stroke but are typically obtrusive and non-intuitive. Here, we provide a rationale for a control strategy suitable for a minimalistic hand exoskeleton. We also report on pilot testing of the strategy, and on a soft actuator design for implementing the strategy. The strategy is based on four experimental observations from studies conducted in our laboratory with unimpaired individuals and stroke survivors. First, using only a pinch grip, unimpaired people can achieve a substantial level of hand function when measured with clinical assessments. Second, the level of achieved function corresponds well with what is necessary to drive daily hand use, as measured by a novel wearable sensor with stroke survivors. Third, even people with severe hand impairment after stroke have a well-preserved ability to control isometric finger flexion force, even though they cannot use their hand to manipulate objects. Fourth, such individuals also exhibit highly correlated forces between fingers. From these observations we propose a control strategy that measures residual finger flexion of digits 3–5 (middle-pinky fingers) to control the force of an exoskeleton assisting in pinch grip. We implemented this “residual force control” strategy using the FINGER exoskeleton and found that unimpaired subjects could intuitively use this strategy to pick up an object and learn to amplify their grip force (Repeated Measures ANOVA, $mathbf{p} pmb{< 004}$). We have also begun developing a soft exoskeleton to implement the residual force control strategy, and we report on the actuator design here. The results of preliminary testing of the actuator show that the actuator could produce a sufficient amount of force ($pmb{13.06} mathbf{N}pmb{pm.33} mathbf{SD})$ to assist the hand.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133489553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Hybrid Force/Velocity Control “With Compliance Estimation via Strain Elastography for Robot Assisted Ultrasound Screening 基于应变弹性成像的机器人辅助超声筛查混合力/速度控制及柔度估计

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Pub Date : 2018-08-01 DOI: 10.1109/BIOROB.2018.8487186

Michael E. Napoli, Christian Freitas, Soumya Goswami, S. McAleavey, M. Doyley, T. M. Howard

{"title":"Hybrid Force/Velocity Control “With Compliance Estimation via Strain Elastography for Robot Assisted Ultrasound Screening","authors":"Michael E. Napoli, Christian Freitas, Soumya Goswami, S. McAleavey, M. Doyley, T. M. Howard","doi":"10.1109/BIOROB.2018.8487186","DOIUrl":"https://doi.org/10.1109/BIOROB.2018.8487186","url":null,"abstract":"Ultrasound scanning provides a noninvasive solution for additional screening in breast cancer detection and could potentially be improved by utilizing a human-robot collaborative system. Alternative ultrasound modalities, such as elastography, offer promising improvements over current sonography cancer detection rates but require stability and knowledge of applied force. A human-robot scanning system could leverage the sonographer's capabilities to select transducer placement while the robot maintains stability during scanning. This paper presents a novel hybrid force velocity controller for ultrasound scanning which utilizes elastography to provide compliance feedback and improve controller performance. We explore the sensitivity of the elastography algorithm to initial elasticity assumptions and analyze the performance gains of compliance feedback. The results of our study show that our proposed controller provides a performance improvement when poor initial tissue compliance estimates are used.","PeriodicalId":382522,"journal":{"name":"2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130294703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11