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Editorial: Modeling Play in Early Infant Development. Front. Neurorobotics (IF 2.574) Pub Date : 2020-08-06 Patricia Shaw,Mark Lee,Qiang Shen,Kathy Hirsh-Pasek,Karen E Adolph,Pierre-Yves Oudeyer,Jill Popp
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Parking Slot Detection on Around-View Images Using DCNN. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-24 Wei Li,Hu Cao,Jiacai Liao,Jiahao Xia,Libo Cao,Alois Knoll
Due to the complex visual environment and incomplete display of parking slots on around-view images, vision-based parking slot detection is a major challenge. Previous studies in this field mostly use the existing models to solve the problem, the steps of which are cumbersome. In this paper, we propose a parking slot detection method that uses directional entrance line regression and classification
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Persistent Effect of Gait Exercise Assist Robot Training on Gait Ability and Lower Limb Function of Patients With Subacute Stroke: A Matched Case-Control Study With Three-Dimensional Gait Analysis. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-24 Yiji Wang,Masahiko Mukaino,Satoshi Hirano,Hiroki Tanikawa,Junya Yamada,Kei Ohtsuka,Takuma Ii,Eiichi Saitoh,Yohei Otaka
Introduction Gait exercise assist robot (GEAR), a gait rehabilitation robot developed for poststroke gait disorder, has been shown to improve walking speed and to improve the poststroke gait pattern. However, the persistence of its beneficial effect has not been clarified. In this matched case-control study, we assessed the durability of the effectiveness of GEAR training in patients with subacute
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AutoPath: Image-Specific Inference for 3D Segmentation. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-24 Dong Sun,Yi Wang,Dong Ni,Tianfu Wang
In recent years, deep convolutional neural networks (CNNs) has made great achievements in the field of medical image segmentation, among which residual structure plays a significant role in the rapid development of CNN-based segmentation. However, the 3D residual networks inevitably bring a huge computational burden to machines for network inference, thus limiting their usages for many real clinical
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Neuromusculoskeletal Arm Prostheses: Personal and Social Implications of Living With an Intimately Integrated Bionic Arm. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-24 Alexandra Middleton,Max Ortiz-Catalan
People with limb loss are for the first time living chronically and uninterruptedly with intimately integrated neuromusculoskeletal prostheses. This new generation of artificial limbs are fixated to the skeleton and operated by bidirectionally transferred neural information. This unprecedented level of human-machine integration is bound to have profound psychosocial effects on the individuals living
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An Adaptive Method for Gait Event Detection of Gait Rehabilitation Robots. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-17 Jing Ye,Hongde Wu,Lishan Wu,Jianjun Long,Yuling Zhang,Gong Chen,Chunbao Wang,Xun Luo,Qinghua Hou,Yi Xu
Accurate gait event detection is necessary for control strategies of gait rehabilitation robots. However, due to personal diversity between individuals, it is a challenge for robots to detect a gait event at various stride frequencies. This paper proposes a novel method for gait event detection of a gait rehabilitation robot using a single inertial sensor mounted on the thigh. A self-adaptive threshold
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Processing Surface EMG Signals for Exoskeleton Motion Control. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-14 Gui Yin,Xiaodong Zhang,Dawei Chen,Hanzhe Li,Jiangcheng Chen,Chaoyang Chen,Stephen Lemos
The surface electromyography (sEMG) signal has been used for volitional control of robotic assistive devices. There are still challenges in improving system performance accuracy and signal processing to remove systematic noise. This study presents procedures and a pilot validation of the EMG-driven speed-control of exoskeleton and integrated treadmill with a goal to provide better interaction between
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A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-10 Yonghao Song,Siqi Cai,Lie Yang,Guofeng Li,Weifeng Wu,Longhan Xie
Background and Objective: Electroencephalography (EEG) can be used to control machines with human intention, especially for paralyzed people in rehabilitation exercises or daily activities. Some effort was put into this but still not enough for online use. To improve the practicality, this study aims to propose an efficient control method based on P300, a special EEG component. Moreover, we have developed
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Path Planning of Mobile Robot With Improved Ant Colony Algorithm and MDP to Produce Smooth Trajectory in Grid-Based Environment. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-09 Hub Ali,Dawei Gong,Meng Wang,Xiaolin Dai
This approach has been derived mainly to improve quality and efficiency of global path planning for a mobile robot with unknown static obstacle avoidance features in grid-based environment. The quality of the global path in terms of smoothness, path consistency and safety can affect the autonomous behavior of a robot. In this paper, the efficiency of Ant Colony Optimization (ACO) algorithm has improved
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Geometric Affordance Perception: Leveraging Deep 3D Saliency With the Interaction Tensor. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-07 Eduardo Ruiz,Walterio Mayol-Cuevas
Agents that need to act on their surroundings can significantly benefit from the perception of their interaction possibilities or affordances. In this paper we combine the benefits of the Interaction Tensor, a straight-forward geometrical representation that captures multiple object-scene interactions, with deep learning saliency for fast parsing of affordances in the environment. Our approach works
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Data-Driven Optimal Assistance Control of a Lower Limb Exoskeleton for Hemiplegic Patients. Front. Neurorobotics (IF 2.574) Pub Date : 2020-07-03 Zhinan Peng,Rui Luo,Rui Huang,Tengbo Yu,Jiangping Hu,Kecheng Shi,Hong Cheng
More recently, lower limb exoskeletons (LLE) have gained considerable interests in strength augmentation, rehabilitation, and walking assistance scenarios. For walking assistance, the LLE is expected to control the affected leg to track the unaffected leg's motion naturally. A critical issue in this scenario is that the exoskeleton system needs to deal with unpredictable disturbance from the patient
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Pneumatic Quasi-Passive Actuation for Soft Assistive Lower Limbs Exoskeleton. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-30 Christian Di Natali,Ali Sadeghi,Alessio Mondini,Eliza Bottenberg,Bernard Hartigan,Adam De Eyto,Leonard O'Sullivan,Eduardo Rocon,Konrad Stadler,Barbara Mazzolai,Darwin G Caldwell,Jesús Ortiz
There is a growing international interest in developing soft wearable robotic devices to improve mobility and daily life autonomy as well as for rehabilitation purposes. Usability, comfort and acceptance of such devices will affect their uptakes in mainstream daily life. The XoSoft EU project developed a modular soft lower-limb exoskeleton to assist people with low mobility impairments. This paper
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An Enhanced Robot Massage System in Smart Homes Using Force Sensing and a Dynamic Movement Primitive. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-29 Chunxu Li,Ashraf Fahmy,Shaoxiang Li,Johann Sienz
With requirements to improve life quality, smart homes, and healthcare have gradually become a future lifestyle. In particular, service robots with human behavioral sensing for private or personal use in the home have attracted a lot of research attention thanks to their advantages in relieving high labor costs and the fatigue of human assistance. In this paper, a novel force-sensing- and robotic learning
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Flexible Spiking CPGs for Online Manipulation During Hexapod Walking. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-26 Beck Strohmer,Poramate Manoonpong,Leon Bonde Larsen
Neural signals for locomotion are influenced both by the neural network architecture and sensory inputs coordinating and adapting the gait to the environment. Adaptation relies on the ability to change amplitude, frequency, and phase of the signals within the sensorimotor loop in response to external stimuli. However, in order to experiment with closed-loop control, we first need a better understanding
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A Path Toward Explainable AI and Autonomous Adaptive Intelligence: Deep Learning, Adaptive Resonance, and Models of Perception, Emotion, and Action. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-25 Stephen Grossberg
Biological neural network models whereby brains make minds help to understand autonomous adaptive intelligence. This article summarizes why the dynamics and emergent properties of such models for perception, cognition, emotion, and action are explainable, and thus amenable to being confidently implemented in large-scale applications. Key to their explainability is how these models combine fast activations
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Exploring Stiffness Modulation in Prosthetic Hands and Its Perceived Function in Manipulation and Social Interaction. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-25 Patricia Capsi-Morales,Cristina Piazza,Manuel G Catalano,Antonio Bicchi,Giorgio Grioli
To physically interact with a rich variety of environments and to match situation-dependent requirements, humans adapt both the force and stiffness of their limbs. Reflecting this behavior in prostheses may promote a more natural and intuitive control and, consequently, improve prostheses acceptance in everyday life. This pilot study proposes a method to control a prosthetic robot hand and its impedance
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Interactive Natural Language Grounding via Referring Expression Comprehension and Scene Graph Parsing. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-25 Jinpeng Mi,Jianzhi Lyu,Song Tang,Qingdu Li,Jianwei Zhang
Natural language provides an intuitive and effective interaction interface between human beings and robots. Currently, multiple approaches are presented to address natural language visual grounding for human-robot interaction. However, most of the existing approaches handle the ambiguity of natural language queries and achieve target objects grounding via dialogue systems, which make the interactions
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Gaze Control of a Robotic Head for Realistic Interaction With Humans. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-17 Jaime Duque-Domingo,Jaime Gómez-García-Bermejo,Eduardo Zalama
When there is an interaction between a robot and a person, gaze control is very important for face-to-face communication. However, when a robot interacts with several people, neurorobotics plays an important role to determine the person to look at and those to pay attention to among the others. There are several factors which can influence the decision: who is speaking, who he/she is speaking to, where
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Editorial: Body Representations, Peripersonal Space, and the Self: Humans, Animals, Robots. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-16 Matej Hoffmann,Pablo Lanillos,Lorenzo Jamone,Alex Pitti,Eszter Somogyi
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Teaching NICO How to Grasp: An Empirical Study on Crossmodal Social Interaction as a Key Factor for Robots Learning From Humans. Front. Neurorobotics (IF 2.574) Pub Date : 2020-06-09 Matthias Kerzel,Theresa Pekarek-Rosin,Erik Strahl,Stefan Heinrich,Stefan Wermter
To overcome novel challenges in complex domestic environments, humanoid robots can learn from human teachers. We propose that the capability for social interaction should be a key factor in this teaching process and benefits both the subjective experience of the human user and the learning process itself. To support our hypothesis, we present a Human-Robot Interaction study on human-assisted visuomotor
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From Near-Optimal Bayesian Integration to Neuromorphic Hardware: A Neural Network Model of Multisensory Integration. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-22 Timo Oess,Maximilian P R Löhr,Daniel Schmid,Marc O Ernst,Heiko Neumann
While interacting with the world our senses and nervous system are constantly challenged to identify the origin and coherence of sensory input signals of various intensities. This problem becomes apparent when stimuli from different modalities need to be combined, e.g., to find out whether an auditory stimulus and a visual stimulus belong to the same object. To cope with this problem, humans and most
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Using Long Short-Term Memory for Building Outdoor Agricultural Machinery. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-16 Chien-Hung Wu,Chun-Yi Lu,Jun-We Zhan,Hsin-Te Wu
Today, climate change has caused a decrease in agricultural output or overall yields that are not as expected; however, with the ongoing population explosion, many undeveloped countries have transformed into emerging countries and have transformed farmland to be used in other types of applications. The resulting decline in agricultural output further increases the severity of the food crisis. In this
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Intention-Related Natural Language Grounding via Object Affordance Detection and Intention Semantic Extraction. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-09 Jinpeng Mi,Hongzhuo Liang,Nikolaos Katsakis,Song Tang,Qingdu Li,Changshui Zhang,Jianwei Zhang
Similar to specific natural language instructions, intention-related natural language queries also play an essential role in our daily life communication. Inspired by the psychology term “affordance” and its applications in Human-Robot interaction, we propose an object affordance-based natural language visual grounding architecture to ground intention-related natural language queries. Formally, we
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Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-08 Mamunur Rashid,Norizam Sulaiman,Anwar P P Abdul Majeed,Rabiu Muazu Musa,Ahmad Fakhri Ab Nasir,Bifta Sama Bari,Sabira Khatun
Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements
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Using Bionics to Restore Sensation to Reconstructed Breasts. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-06 Stacy T Lindau,Sliman J Bensmaia
Mastectomy often leads to a complete desensitization of the chest, which in turn can give rise to diminished sexual function and to disembodiment of the breasts. One approach to mitigate the sensory consequences of mastectomy is to leverage technology that has been developed for the restoration of sensation in bionic hands. Specifically, sensors embedded under the skin of the nipple-areolar complex
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Automatic Generation of Object Shapes With Desired Affordances Using Voxelgrid Representation. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-03 Mihai Andries,Atabak Dehban,José Santos-Victor
3D objects (artifacts) are made to fulfill functions. Designing an object often starts with defining a list of functionalities or affordances (action possibilities) that it should provide, known as functional requirements. Today, designing 3D object models is still a slow and difficult activity, with few Computer-Aided Design (CAD) tools capable to explore the design solution space. The purpose of
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A Prosthetic Shank With Adaptable Torsion Stiffness and Foot Alignment. Front. Neurorobotics (IF 2.574) Pub Date : 2020-04-03 Jochen Schuy,Nadine Stech,Graham Harris,Philipp Beckerle,Saeed Zahedi,Stephan Rinderknecht
Torsion adapters in lower limb prostheses aim to increase comfort, mobility and health of users by allowing rotation in the transversal plane. A preliminary study with two transtibial amputees indicated correlations between torsional stiffness and foot alignment to increase comfort and stability of the user depending on the gait situation and velocity. This paper presents the design and proof-of-concept
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Generalize Robot Learning From Demonstration to Variant Scenarios With Evolutionary Policy Gradient. Front. Neurorobotics (IF 2.574) Pub Date : 2020-03-27 Junjie Cao,Weiwei Liu,Yong Liu,Jian Yang
There has been substantial growth in research on the robot automation, which aims to make robots capable of directly interacting with the world or human. Robot learning for automation from human demonstration is central to such situation. However, the dependence of demonstration restricts robot to a fixed scenario, without the ability to explore in variant situations to accomplish the same task as
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Design of Muscle Reflex Control for Upright Standing Push-Recovery Based on a Series Elastic Robot Ankle Joint. Front. Neurorobotics (IF 2.574) Pub Date : 2020-03-17 Yuyang Cao,Kui Xiang,Biwei Tang,Zhaojie Ju,Muye Pang
In physical human–robot interaction environment, ankle joint muscle reflex control remains significant and promising in human bipedal stance. The reflex control mechanism contains rich information of human joint dynamic behavior, which is valuable in the application of real-time decoding motion intention. Thus, investigating the human muscle reflex mechanism is not only meaningful in human physiology
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A Review of Robot-Assisted Lower-Limb Stroke Therapy: Unexplored Paths and Future Directions in Gait Rehabilitation. Front. Neurorobotics (IF 2.574) Pub Date : 2020-03-16 Bradley Hobbs,Panagiotis Artemiadis
Stroke affects one out of every six people on Earth. Approximately 90% of stroke survivors have some functional disability with mobility being a major impairment, which not only affects important daily activities but also increases the likelihood of falling. Originally intended to supplement traditional post-stroke gait rehabilitation, robotic systems have gained remarkable attention in recent years
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Visual-Haptic Size Estimation in Peripersonal Space. Front. Neurorobotics (IF 2.574) Pub Date : 2020-03-13 Nikolaos Katzakis,Lihan Chen,Frank Steinicke
In perceptual psychology, estimations of visual depth and size under different spatial layouts have been extensively studied. However, research evidence in virtual environments (VE) is relatively lacking. The emergence of human-computer interaction (HCI) and virtual reality (VR) has raised the question of how human operators perform actions based on the estimation of visual properties in VR, especially
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Development of an Improved Rotational Orthosis for Walking With Arm Swing and Active Ankle Control. Front. Neurorobotics (IF 2.574) Pub Date : 2020-03-10 Zaile Mu,Qiuju Zhang,Guo-Yuan Yang,Le Xie,Juan Fang
Based on interlimb neural coupling, gait robotic systems should produce walking-like movement in both upper and lower limbs for effective walking restoration. Two orthoses were previously designed in our lab to provide passive walking with arm swing. However, an active system for walking with arm swing is desirable to serve as a testbed for investigation of interlimb neural coupling in response to
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Robustness Through Simplicity: A Minimalist Gateway to Neurorobotic Flight Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-27 Simon D. Levy
In attempting to build neurorobotic systems based on flying animals, engineers have come to rely on existing firmware and simulation tools designed for miniature aerial vehicles (MAVs). Although they provide a valuable platform for the collection of data for Deep Learning and related AI approaches, such tools are deliberately designed to be general (supporting air, ground, and water vehicles) and feature-rich
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Evolving Toward Subject-Specific Gait Rehabilitation Through Single-Joint Resistive Force Interventions Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-17 S. Srikesh Iyer; Joel V. Joseph; Vineet Vashista
Walking is one of the most relevant tasks that a person performs in their daily routine. Despite its mechanical complexities, any change in the external conditions that applies some external perturbation, or in the human musculoskeletal system that limits an individual's movement, entails a motor response that can either be compensatory or adaptive in nature. Incidentally, with aging or due to the
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Cross-Talk of Low-Level Sensory and High-Level Cognitive Processing: Development, Mechanisms, and Relevance for Cross-Modal Abilities of the Brain. Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-14 Xiaxia Xu,Ileana L Hanganu-Opatz,Malte Bieler
The emergence of cross-modal learning capabilities requires the interaction of neural areas accounting for sensory and cognitive processing. Convergence of multiple sensory inputs is observed in low-level sensory cortices including primary somatosensory (S1), visual (V1), and auditory cortex (A1), as well as in high-level areas such as prefrontal cortex (PFC). Evidence shows that local neural activity
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An Intuitive End-to-End Human-UAV Interaction System for Field Exploration. Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-14 Ran Jiao,Zhaowei Wang,Ruihang Chu,Mingjie Dong,Yongfeng Rong,Wusheng Chou
This paper presents an intuitive end-to-end interaction system between a human and a hexacopter Unmanned Aerial Vehicle (UAV) for field exploration in which the UAV can be commanded by natural human poses. Moreover, LEDs installed on the UAV are used to communicate the state and intents of the UAV to the human as feedback throughout the interaction. A real time multi-human pose estimation system is
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Neurorobotics Workshop for High School Students Promotes Competence and Confidence in Computational Neuroscience. Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-13 Christopher A Harris,Lucia Guerri,Stanislav Mircic,Zachary Reining,Marcio Amorim,Ðorđe Jović,William Wallace,Jennifer DeBoer,Gregory J Gage
Understanding the brain is a fascinating challenge, captivating the scientific community and the public alike. The lack of effective treatment for most brain disorders makes the training of the next generation of neuroscientists, engineers and physicians a key concern. Over the past decade there has been a growing effort to introduce neuroscience in primary and secondary schools, however, hands-on
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Semantic Knowledge Representation for Strategic Interactions in Dynamic Situations. Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-13 Carlos Calvo Tapia,José Antonio Villacorta-Atienza,Sergio Díez-Hermano,Maxim Khoruzhko,Sergey Lobov,Ivan Potapov,Abel Sánchez-Jiménez,Valeri A Makarov
Evolved living beings can anticipate the consequences of their actions in complex multilevel dynamic situations. This ability relies on abstracting the meaning of an action. The underlying brain mechanisms of such semantic processing of information are poorly understood. Here we show how our novel concept, known as time compaction, provides a natural way of representing semantic knowledge of actions
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Small-Sized Reconfigurable Quadruped Robot With Multiple Sensory Feedback for Studying Adaptive and Versatile Behaviors Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-10 Tao Sun; Xiaofeng Xiong; Zhendong Dai; Poramate Manoonpong
Self-organization of locomotion characterizes the feature of automatically spontaneous gait generation without preprogrammed limb movement coordination. To study this feature in quadruped locomotion, we propose here a new open-source, small-sized reconfigurable quadruped robot, called Lilibot, with multiple sensory feedback and its physical simulation. Lilibot was designed as a friendly quadrupedal
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Modeling and Control of a Cable-Driven Rotary Series Elastic Actuator for an Upper Limb Rehabilitation Robot Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-06 Qiang Zhang; Dingyang Sun; Wei Qian; Xiaohui Xiao; Zhao Guo
This paper focuses on the design, modeling, and control of a novel remote actuation, including a compact rotary series elastic actuator (SEA) and Bowden cable. This kind of remote actuation is used for an upper limb rehabilitation robot (ULRR) with four powered degrees of freedom (DOFs). The SEA mainly consists of a DC motor with planetary gearheads, inner/outer sleeves, and eight linearly translational
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Learning to Predict Perceptual Distributions of Haptic Adjectives. Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-06 Benjamin A Richardson,Katherine J Kuchenbecker
When humans touch an object with their fingertips, they can immediately describe its tactile properties using haptic adjectives, such as hardness and roughness; however, human perception is subjective and noisy, with significant variation across individuals and interactions. Recent research has worked to provide robots with similar haptic intelligence but was focused on identifying binary haptic adjectives
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Statistical Inter-stimulus Interval Window Estimation for Transient Neuromodulation via Paired Mechanical and Brain Stimulation. Front. Neurorobotics (IF 2.574) Pub Date : 2020-02-03 Euisun Kim,Waiman Meinhold,Minoru Shinohara,Jun Ueda
For achieving motor recovery in individuals with sensorimotor deficits, augmented activation of the appropriate sensorimotor system, and facilitated induction of neural plasticity are essential. An emerging procedure that combines peripheral nerve stimulation and its associative stimulation with central brain stimulation is known to enhance the excitability of the motor cortex. In order to effectively
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Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-31 Sonia F. Roberts; Daniel E. Koditschek; Lisa J. Miracchi
Evidence from empirical literature suggests that explainable complex behaviors can be built from structured compositions of explainable component behaviors with known properties. Such component behaviors can be built to directly perceive and exploit affordances. Using six examples of recent research in legged robot locomotion, we suggest that robots can be programmed to effectively exploit affordances
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Crossmodal Language Comprehension-Psycholinguistic Insights and Computational Approaches. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-31 Özge Alaçam,Xingshan Li,Wolfgang Menzel,Tobias Staron
Crossmodal interaction in situated language comprehension is important for effective and efficient communication. The relationship between linguistic and visual stimuli provides mutual benefit: While vision contributes, for instance, information to improve language understanding, language in turn plays a role in driving the focus of attention in the visual environment. However, language and vision
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Online Natural Myocontrol of Combined Hand and Wrist Actions Using Tactile Myography and the Biomechanics of Grasping Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-30 Mathilde Connan; Risto Kõiva; Claudio Castellini
Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all
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SAUV—A Bio-Inspired Soft-Robotic Autonomous Underwater Vehicle Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-29 Fabian Plum; Susanna Labisch; Jan-Henning Dirks
Autonomous and remotely operated underwater vehicles allow us to reach places which have previously been inaccessible and perform complex repair, exploration and analysis tasks. As their navigation is not infallible, they may cause severe damage to themselves and their often fragile surroundings, such as flooded caves, coral reefs, or even accompanying divers in case of a collision. In this study,
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Semi-Autonomous Robotic Arm Reaching With Hybrid Gaze-Brain Machine Interface. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-24 Hong Zeng,Yitao Shen,Xuhui Hu,Aiguo Song,Baoguo Xu,Huijun Li,Yanxin Wang,Pengcheng Wen
Recent developments in the non-muscular human-robot interface (HRI) and shared control strategies have shown potential for controlling the assistive robotic arm by people with no residual movement or muscular activity in upper limbs. However, most non-muscular HRIs only produce discrete-valued commands, resulting in non-intuitive and less effective control of the dexterous assistive robotic arm. Furthermore
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Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-24 Lidor Bahar,Yarden Sharon,Ilana Nisky
Robotic assisted minimally invasive surgery (RAMIS) systems present many advantages to the surgeon and patient over open and standard laparoscopic surgery. However, haptic feedback, which is crucial for the success of many surgical procedures, is still an open challenge in RAMIS. Understanding the way that haptic feedback affects performance and learning can be useful in the development of haptic feedback
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Droplet-Transmitted Infection Risk Ranking Based on Close Proximity Interaction. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-21 Shihui Guo,Jubo Yu,Xinyu Shi,Hongran Wang,Feibin Xie,Xing Gao,Min Jiang
We propose an automatic method to identify people who are potentially-infected by droplet-transmitted diseases. This high-risk group of infection was previously identified by conducting large-scale visits/interviews, or manually screening among tons of recorded surveillance videos. Both are time-intensive and most likely to delay the control of communicable diseases like influenza. In this paper, we
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Prerequisites for an Artificial Self Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-17 Verena V. Hafner; Pontus Loviken; Antonio Pico Villalpando; Guido Schillaci
Traditionally investigated in philosophy, body ownership and agency—two main components of the minimal self—have recently gained attention from other disciplines, such as brain, cognitive and behavioral sciences, and even robotics and artificial intelligence. In robotics, intuitive human interaction in natural and dynamic environments becomes more and more important, and requires skills such as self-other
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Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-17 Vieri Giuliano Santucci,Pierre-Yves Oudeyer,Andrew Barto,Gianluca Baldassarre
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A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-17 Daniele Esposito,Emilio Andreozzi,Gaetano D Gargiulo,Antonio Fratini,Giovanni D'Addio,Ganesh R Naik,Paolo Bifulco
Human machine interfaces (HMIs) are employed in a broad range of applications, spanning from assistive devices for disability to remote manipulation and gaming controllers. In this study, a new piezoresistive sensors array armband is proposed for hand gesture recognition. The armband encloses only three sensors targeting specific forearm muscles, with the aim to discriminate eight hand movements. Each
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A Fireworks Algorithm Based on Transfer Spark for Evolutionary Multitasking. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-17 Zhiwei Xu,Kai Zhang,Xin Xu,Juanjuan He
In recent years, lots of multifactorial optimization evolutionary algorithms have been developed to optimize multiple tasks simultaneously, which improves the overall efficiency using implicit genetic complementarity between different tasks. In this paper, a novel multitask fireworks algorithm is proposed with novel transfer sparks to solve multitask optimization problems. For each task, some transfer
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A Privacy-Preserving Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-14 Chen Zhang,Xiongwei Hu,Yu Xie,Maoguo Gong,Bin Yu
Recently, multi-task learning (MTL) has been extensively studied for various face processing tasks, including face detection, landmark localization, pose estimation, and gender recognition. This approach endeavors to train a better model by exploiting the synergy among the related tasks. However, the raw face dataset used for training often contains sensitive and private information, which can be maliciously
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Lizard Brain: Tackling Locally Low-Dimensional Yet Globally Complex Organization of Multi-Dimensional Datasets. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-09 Jonathan Bac,Andrei Zinovyev
Machine learning deals with datasets characterized by high dimensionality. However, in many cases, the intrinsic dimensionality of the datasets is surprisingly low. For example, the dimensionality of a robot's perception space can be large and multi-modal but its variables can have more or less complex non-linear interdependencies. Thus multidimensional data point clouds can be effectively located
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Indoor Simulated Training Environment for Brain-Controlled Wheelchair Based on Steady-State Visual Evoked Potentials. Front. Neurorobotics (IF 2.574) Pub Date : 2020-01-08 Ming Liu,Kangning Wang,Xiaogang Chen,Jing Zhao,Yuanyuan Chen,Huiquan Wang,Jinhai Wang,Shengpu Xu
Brain-controlled wheelchair (BCW) has the potential to improve the quality of life for people with motor disabilities. A lot of training is necessary for users to learn and improve BCW control ability and the performances of BCW control are crucial for patients in daily use. In consideration of safety and efficiency, an indoor simulated training environment is built up in this paper to improve the
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Toward a Gecko-Inspired, Climbing Soft Robot. Front. Neurorobotics (IF 2.574) Pub Date : 2019-12-19 Lars Schiller,Arthur Seibel,Josef Schlattmann
In this paper, we present a gecko-inspired soft robot that is able to climb inclined, flat surfaces. By changing the design of the previous version, the energy consumption of the robot could be reduced, and at the same time, its ability to climb and its speed of movement could be increased. As a result, the new prototype consumes only about a third of the energy of the previous version and manages
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Walking Human Detection Using Stereo Camera Based on Feature Classification Algorithm of Second Re-projection Error. Front. Neurorobotics (IF 2.574) Pub Date : 2019-12-18 Shuhuan Wen,Sen Wang,ZhiShang Zhang,Xuebo Zhang,Dan Zhang
This paper presents a feature classification method based on vision sensor in dynamic environment. Aiming at the detected targets, a double-projection error based on orb and surf is proposed, which combines texture constraints and region constraints to achieve accurate feature classification in four different environments. For dynamic targets with different velocities, the proposed classification framework
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Muscle Synergy Constraints Do Not Improve Estimates of Muscle Activity From Static Optimization During Gait for Unimpaired Children or Children With Cerebral Palsy. Front. Neurorobotics (IF 2.574) Pub Date : 2019-12-17 Benjamin R Shuman,Marije Goudriaan,Kaat Desloovere,Michael H Schwartz,Katherine M Steele
Neuromusculoskeletal simulation provides a promising platform to inform the design of assistive devices or inform rehabilitation. For these applications, a simulation must be able to accurately represent the person of interest, such as an individual with a neurologic injury. If a simulation fails to predict how an individual recruits and coordinates their muscles during movement, it will have limited
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Flexible Coordination of Flexible Limbs: Decentralized Control Scheme for Inter- and Intra-Limb Coordination in Brittle Stars' Locomotion. Front. Neurorobotics (IF 2.574) Pub Date : 2019-12-13 Takeshi Kano,Daichi Kanauchi,Tatsuya Ono,Hitoshi Aonuma,Akio Ishiguro
Conventional mobile robots have difficulties adapting to unpredictable environments or performing adequately after undergoing physical damages in realtime operation, unlike animals. We address this issue by focusing on brittle stars, an echinoderm related to starfish. Most brittle stars have five flexible arms, and they can coordinate among the arms (i.e., inter-arm coordination) as well as the many
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