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Frontiers in Neurorobotics

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https://www.readbyqxmd.com/read/28804454/an-evaluation-of-the-design-and-usability-of-a-novel-robotic-bilateral-arm-rehabilitation-device-for-patients-with-stroke
#1
Yu-Cheng Pei, Jean-Lon Chen, Alice M K Wong, Kevin C Tseng
STUDY DESIGN: Case series. EVIDENCE LEVEL: IV (case series). INTRODUCTION: Robot-assisted therapy for upper limb rehabilitation is an emerging research topic and its design process must integrate engineering, neurological pathophysiology, and clinical needs. PURPOSE OF THE STUDY: This study developed/evaluated the usefulness of a novel rehabilitation device, the MirrorPath, designed for the upper limb rehabilitation of patients with hemiplegic stroke...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28790910/hybrid-brain-computer-interface-techniques-for-improved-classification-accuracy-and-increased-number-of-commands-a-review
#2
REVIEW
Keum-Shik Hong, Muhammad Jawad Khan
In this article, non-invasive hybrid brain-computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28769781/enhancing-classification-performance-of-functional-near-infrared-spectroscopy-brain-computer-interface-using-adaptive-estimation-of-general-linear-model-coefficients
#3
Nauman Khalid Qureshi, Noman Naseer, Farzan Majeed Noori, Hammad Nazeer, Rayyan Azam Khan, Sajid Saleem
In this paper, a novel methodology for enhanced classification of functional near-infrared spectroscopy (fNIRS) signals utilizable in a two-class [motor imagery (MI) and rest; mental rotation (MR) and rest] brain-computer interface (BCI) is presented. First, fNIRS signals corresponding to MI and MR are acquired from the motor and prefrontal cortex, respectively, afterward, filtered to remove physiological noises. Then, the signals are modeled using the general linear model, the coefficients of which are adaptively estimated using the least squares technique...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28747884/geomagnetic-navigation-of-autonomous-underwater-vehicle-based-on-multi-objective-evolutionary-algorithm
#4
Hong Li, Mingyong Liu, Feihu Zhang
This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28747883/obstacle-avoidance-and-target-acquisition-for-robot-navigation-using-a-mixed-signal-analog-digital-neuromorphic-processing-system
#5
Moritz B Milde, Hermann Blum, Alexander Dietmüller, Dora Sumislawska, Jörg Conradt, Giacomo Indiveri, Yulia Sandamirskaya
Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28725192/commentary-proceedings-of-the-first-workshop-on-peripheral-machine-interfaces-going-beyond-traditional-surface-electromyography
#6
COMMENT
Philipp Beckerle
No abstract text is available yet for this article.
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28690514/synergistic-effects-on-the-elderly-people-s-motor-control-by-wearable-skin-stretch-device-combined-with-haptic-joystick
#7
Han U Yoon, Namita Anil Kumar, Pilwon Hur
Cutaneous sensory feedback can be used to provide additional sensory cues to a person performing a motor task where vision is a dominant feedback signal. A haptic joystick has been widely used to guide a user by providing force feedback. However, the benefit of providing force feedback is still debatable due to performance dependency on factors such as the user's skill-level, task difficulty. Meanwhile, recent studies have shown the feasibility of improving a motor task performance by providing skin-stretch feedback...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28676752/an-adaptive-neuromuscular-controller-for-assistive-lower-limb-exoskeletons-a-preliminary-study-on-subjects-with-spinal-cord-injury
#8
Amy R Wu, Florin Dzeladini, Tycho J H Brug, Federica Tamburella, Nevio L Tagliamonte, Edwin H F van Asseldonk, Herman van der Kooij, Auke J Ijspeert
Versatility is important for a wearable exoskeleton controller to be responsive to both the user and the environment. These characteristics are especially important for subjects with spinal cord injury (SCI), where active recruitment of their own neuromuscular system could promote motor recovery. Here we demonstrate the capability of a novel, biologically-inspired neuromuscular controller (NMC) which uses dynamical models of lower limb muscles to assist the gait of SCI subjects. Advantages of this controller include robustness, modularity, and adaptability...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28676751/the-role-of-autobiographical-memory-in-the-development-of-a-robot-self
#9
Gregoire Pointeau, Peter Ford Dominey
This article briefly reviews research in cognitive development concerning the nature of the human self. It then reviews research in developmental robotics that has attempted to retrace parts of the developmental trajectory of the self. This should be of interest to developmental psychologists, and researchers in developmental robotics. As a point of departure, one of the most characteristic aspects of human social interaction is cooperation-the process of entering into a joint enterprise to achieve a common goal...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28659784/effects-of-assist-as-needed-upper-extremity-robotic-therapy-after-incomplete-spinal-cord-injury-a-parallel-group-controlled-trial
#10
John Michael Frullo, Jared Elinger, Ali Utku Pehlivan, Kyle Fitle, Kathryn Nedley, Gerard E Francisco, Fabrizio Sergi, Marcia K O'Malley
BACKGROUND: Robotic rehabilitation of the upper limb following neurological injury has been supported through several large clinical studies for individuals with chronic stroke. The application of robotic rehabilitation to the treatment of other neurological injuries is less developed, despite indications that strategies successful for restoration of motor capability following stroke may benefit individuals with incomplete spinal cord injury (SCI) as well. Although recent studies suggest that robot-aided rehabilitation might be beneficial after incomplete SCI, it is still unclear what type of robot-aided intervention contributes to motor recovery...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28649197/a-minimal-model-describing-hexapedal-interlimb-coordination-the-tegotae-based-approach
#11
Dai Owaki, Masashi Goda, Sakiko Miyazawa, Akio Ishiguro
Insects exhibit adaptive and versatile locomotion despite their minimal neural computing. Such locomotor patterns are generated via coordination between leg movements, i.e., an interlimb coordination, which is largely controlled in a distributed manner by neural circuits located in thoracic ganglia. However, the mechanism responsible for the interlimb coordination still remains elusive. Understanding this mechanism will help us to elucidate the fundamental control principle of animals' agile locomotion and to realize robots with legs that are truly adaptive and could not be developed solely by conventional control theories...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28611621/whole-body-awareness-for-controlling-a-robotic-transfemoral-prosthesis
#12
Andrea Parri, Elena Martini, Joost Geeroms, Louis Flynn, Guido Pasquini, Simona Crea, Raffaele Molino Lova, Dirk Lefeber, Roman Kamnik, Marko Munih, Nicola Vitiello
Restoring locomotion functionality of transfemoral amputees is essential for early rehabilitation treatment and for preserving mobility and independence in daily life. Research in wearable robotics fostered the development of innovative active mechatronic lower-limb prostheses designed with the goal to reduce the cognitive and physical effort of lower-limb amputees in rehabilitation and daily life activities. To ensure benefits to the users, active mechatronic prostheses are expected to be aware of the user intention and properly interact in a closed human-in-the-loop paradigm...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28588473/a-human-robot-interaction-perspective-on-assistive-and-rehabilitation-robotics
#13
Philipp Beckerle, Gionata Salvietti, Ramazan Unal, Domenico Prattichizzo, Simone Rossi, Claudio Castellini, Sandra Hirche, Satoshi Endo, Heni Ben Amor, Matei Ciocarlie, Fulvio Mastrogiovanni, Brenna D Argall, Matteo Bianchi
Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human-robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28588472/key-insights-into-hand-biomechanics-human-grip-stiffness-can-be-decoupled-from-force-by-cocontraction-and-predicted-from-electromyography
#14
Hannes Höppner, Maximilian Große-Dunker, Georg Stillfried, Justin Bayer, Patrick van der Smagt
We investigate the relation between grip force and grip stiffness for the human hand with and without voluntary cocontraction. Apart from gaining biomechanical insight, this issue is particularly relevant for variable-stiffness robotic systems, which can independently control the two parameters, but for which no clear methods exist to design or efficiently exploit them. Subjects were asked in one task to produce different levels of force, and stiffness was measured. As expected, this task reveals a linear coupling between force and stiffness...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28503145/a-neural-dynamic-architecture-for-concurrent-estimation-of-object-pose-and-identity
#15
Oliver Lomp, Christian Faubel, Gregor Schöner
Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single view of each object. Input features are color and edge histograms from a localized area that is updated during processing. The system finds the best-matching view for the object in a novel input image while concurrently estimating the object's pose, aligning the learned view with current input...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28487646/human-inspired-eigenmovement-concept-provides-coupling-free-sensorimotor-control-in-humanoid-robot
#16
Alexei V Alexandrov, Vittorio Lippi, Thomas Mergner, Alexander A Frolov, Georg Hettich, Dusan Husek
Control of a multi-body system in both robots and humans may face the problem of destabilizing dynamic coupling effects arising between linked body segments. The state of the art solutions in robotics are full state feedback controllers. For human hip-ankle coordination, a more parsimonious and theoretically stable alternative to the robotics solution has been suggested in terms of the Eigenmovement (EM) control. Eigenmovements are kinematic synergies designed to describe the multi DoF system, and its control, with a set of independent, and hence coupling-free, scalar equations...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28450834/communication-and-inference-of-intended-movement-direction-during-human-human-physical-interaction
#17
Keivan Mojtahedi, Bryan Whitsell, Panagiotis Artemiadis, Marco Santello
Of particular interest to the neuroscience and robotics communities is the understanding of how two humans could physically collaborate to perform motor tasks such as holding a tool or moving it across locations. When two humans physically interact with each other, sensory consequences and motor outcomes are not entirely predictable as they also depend on the other agent's actions. The sensory mechanisms involved in physical interactions are not well understood. The present study was designed (1) to quantify human-human physical interactions where one agent ("follower") has to infer the intended or imagined-but not executed-direction of motion of another agent ("leader") and (2) to reveal the underlying strategies used by the dyad...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28446872/a-neurocomputational-model-of-goal-directed-navigation-in-insect-inspired-artificial-agents
#18
Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta
Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28443015/cross-subject-eeg-feature-selection-for-emotion-recognition-using-transfer-recursive-feature-elimination
#19
Zhong Yin, Yongxiong Wang, Li Liu, Wei Zhang, Jianhua Zhang
Using machine-learning methodologies to analyze EEG signals becomes increasingly attractive for recognizing human emotions because of the objectivity of physiological data and the capability of the learning principles on modeling emotion classifiers from heterogeneous features. However, the conventional subject-specific classifiers may induce additional burdens to each subject for preparing multiple-session EEG data as training sets. To this end, we developed a new EEG feature selection approach, transfer recursive feature elimination (T-RFE), to determine a set of the most robust EEG indicators with stable geometrical distribution across a group of training subjects and a specific testing subject...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28420977/development-and-training-of-a-neural-controller-for-hind-leg-walking-in-a-dog-robot
#20
Alexander Hunt, Nicholas Szczecinski, Roger Quinn
Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal's body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few "synthetic nervous systems" have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward...
2017: Frontiers in Neurorobotics
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