Advancing the detection of steady-state visual evoked potentials in brain-computer interfaces

© 2016 IOP Publishing Ltd. Objective. Spatial filtering has proved to be a powerful pre-processing step in detection of steady-state visual evoked potentials and boosted typical detection rates both in offline analysis and online SSVEP-based brain-computer interface applications. State-of-the-art detection methods and the spatial filters used thereby share many common foundations as they all build upon the second order statistics of the acquired Electroencephalographic (EEG) data, that is, its spatial autocovariance and cross-covariance with what is assumed to be a pure SSVEP response. The present study aims at highlighting the similarities and differences between these methods. Approach. We consider the canonical correlation analysis (CCA) method as a basis for the theoretical and empirical (with real EEG data) analysis of the state-of-the-art detection methods and the spatial filters used thereby. We build upon the findings of this analysis and prior research and propose a new detection method (CVARS) that combines the power of the canonical variates and that of the autoregressive spectral analysis in estimating the signal and noise power levels. Main results. We found that the multivariate synchronization index method and the maximum contrast combination method are variations of the CCA method. All three methods were found to provide relatively unreliable detections in low signal-to-noise ratio (SNR) regimes. CVARS and the minimum energy combination methods were found to provide better estimates for different SNR levels. Significance. Our theoretical and empirical results demonstrate that the proposed CVARS method outperforms other state-of-the-art detection methods when used in an unsupervised fashion. Furthermore, when used in a supervised fashion, a linear classifier learned from a short training session is able to estimate the hidden user intention, including the idle state (when the user is not attending to any stimulus), rapidly, accurately and reliably

The Field of Telerobotics

The Field of Telerobotic

A new interaction force decomposition maximizing compensating forces under physical work constraints

Decomposition of interaction forces in manipulation tasks has a long research tradition. Interaction forces are often split into robustness-reflective and accelerating forces. While this decomposition is typically performed for the synthesis of interaction forces to be applied for example in the context of robotic grasping, less attention has been paid to the analysis of measured, human interaction forces. Here we present a new decomposition approach for interaction force analysis. It extends the intuitive solution known in literature for the two finger grasp and combines it with a physically motivated bounding constraint, which allows the maximization of robustness reflective forces. Advantages of our approach are illustrated with an example and are compared to existing decomposition approaches. In contrast to existing approaches the new approach is not limited in the number of interaction points and incorporates forces which are physically possible only

Decision-making model for adaptive impedance control of teleoperation systems

© 2008-2011 IEEE. This paper presents a haptic assistance strategy for teleoperation that makes a task and situation-specific compromise between improving tracking performance or human-machine interaction in partially structured environments via the scheduling of the parameters of an admittance controller. The proposed assistance strategy builds on decision-making models and combines one of them with impedance control techniques that are standard in bilateral teleoperation systems. Even though several decision-making models have been proposed in cognitive science, their application to assisted teleoperation and assisted robotics has hardly been explored yet. Experimental data supports the Drift-Diffusion model as a suitable scheduling strategy for haptic shared control, in which the assistance mechanism can be adapted via the parameters of reward functions. Guidelines to tune the decision making model are presented. The influence of the reward structure on the realized haptic assistances is evaluated in a user study and results are compared to the no assistance and human assistance case

Enhancing the Command-Following Bandwidth for Transparent Bilateral Teleoperation

© 2018 IEEE. Enhancing transparency of a teleoperation system by increasing the command-following bandwidth has not received lots of attention so far. This is considered a challenging task since in a teleoperation system the command-following bandwidth of the slave robot motion controller cannot be increased with a conventional motion controller as the desired trajectory is instantaneously commanded by the human user and thus, cannot be considered to be given in a pre-computed, smooth second order derivative form. We propose a method to increase the command-following bandwidth by extending the previously introduced Successive Stiffness Increment (SSI) approach to bilateral teleoperation. The approach allows realizing a very high motion controller gain, which cannot be realized with a conventional bilateral teleoperation controller as confirmed by experimental results

Evaluation studies of robotic rollators by the user perspective: A systematic review

Background: Robotic rollators enhance the basic functions of established devices by technically advanced physical, cognitive, or sensory support to increase autonomy in persons with severe impairment. In the evaluation of such Ambient Assisted Living solutions, both the technical and user perspectives are important to prove usability, effectiveness, and safety, and to ensure adequate device application.Objective: The aim of this systematic review is to summarize the methodology of studies evaluating robotic rollators with focus on the user perspective and to give recommendations for future evaluation studies.Methods: A systematic literature search up to December 31, 2014 was conducted based on the Cochrane Review methodology using the electronic databases PubMed and IEEE Xplore. Articles were selected according to the following inclusion criteria: Evaluation studies of robotic rollators documenting human-robot interaction, no case reports, published in English language.Results: Twenty-eight studies were identified that met the predefined inclusion criteria. Large heterogeneity in the definitions of the target user group, study populations, study designs, and assessment methods was found across the included studies. No generic methodology to evaluate robotic rollators could be identified. We found major methodological shortcomings related to insufficient sample descriptions and sample sizes, and lack of appropriate, standardized and validated assessment methods. Long-term use in habitual environment was also not evaluated.Conclusions: Apart from the heterogeneity, methodological deficits in most of the identified studies became apparent. Recommendations for future evaluation studies include: clear definition of target user group, adequate selection of subjects, inclusion of other assistive mobility devices for comparison, evaluation of the habitual use of advanced prototypes, adequate assessment strategy with established, standardized and validated methods, and statistical analysis of study results. Assessment strategies may additionally focus on specific functionalities of the robotic rollators allowing an individually tailored assessment of innovative features to document their added value

Contributions of the PPC to online control of visually guided reaching movements assessed with fMRI-Guided TMS

The posterior parietal cortex (PPC) plays an important role in controlling voluntary movements by continuously integrating sensory information about body state and the environment. We tested which subregions of the PPC contribute to the processing of target- and body-related visual information while reaching for an object, using a reaching paradigm with 2 types of visual perturbation: displacement of the visual target and displacement of the visual feedback about the hand position. Initially, functional magnetic resonance imaging (fMRI) was used to localize putative target areas involved in online corrections of movements in response to perturbations. The causal contribution of these areas to online correction was tested in subsequent neuronavigated transcranial magnetic stimulation (TMS) experiments. Robust TMS effects occurred at distinct anatomical sites along the anterior intraparietal sulcus (aIPS) and the anterior part of the supramarginal gyrus for both perturbations. TMS over neighboring sites did not affect online control. Our results support the hypothesis that the aIPS is more generally involved in visually guided control of movements, independent of body effectors and nature of the visual information. Furthermore, they suggest that the human network of PPC subregions controlling goal-directed visuomotor processes extends more inferiorly than previously thought. Our results also point toward a good spatial specificity of the TMS effects. © 2010 The Author

Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch

© 2016 IEEE. Giving robots the ability to classify surface textures requires appropriate sensors and algorithms. Inspired by the biology of human tactile perception, we implement a neurorobotic texture classifier with a recurrent spiking neural network, using a novel semisupervised approach for classifying dynamic stimuli. Input to the network is supplied by accelerometers mounted on a robotic arm. The sensor data are encoded by a heterogeneous population of neurons, modeled to match the spiking activity of mechanoreceptor cells. This activity is convolved by a hidden layer using bandpass filters to extract nonlinear frequency information from the spike trains. The resulting high-dimensional feature representation is then continuously classified using a neurally implemented support vector machine. We demonstrate that our system classifies 18 metal surface textures scanned in two opposite directions at a constant velocity. We also demonstrate that our approach significantly improves upon a baseline model that does not use the described feature extraction. This method can be performed in real-time using neuromorphic hardware, and can be extended to other applications that process dynamic stimuli online

CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments

Rescue missions in mountain environments are hardly achievable by standard legged robots - because of the high slopes - or by flying robots - because of limited payload capacity. We present a novel concept for a rope-aided climbing robot, which can negotiate up-to-vertical slopes and carry heavy payloads. The robot is attached to the mountain through a rope, and is equipped with a leg to push against the mountain and initiate jumping maneuvers. Between jumps, a hoist is used to wind/unwind the rope to move vertically and affect the lateral motion. This simple (yet effective) two-fold actuation allows the system to achieve high safety and energy efficiency. Indeed, the rope prevents the robot from falling, while compensating for most of its weight, drastically reducing the effort required by the leg actuator. We also present an optimal control strategy to generate point-to-point trajectories overcoming an obstacle. We achieve fast computation time ($<$1 s) thanks to the use of a custom simplified robot model. We validated the generated optimal movements in Gazebo simulations with a complete robot model, showing the effectiveness of the proposed approach, and confirming the interest of our concept. Finally, we performed a reachability analysis showing that the region of achievable targets is strongly affected by the friction properties of the foot-wall contact.Comment: 6 page

A systematic review of study results reported for the evaluation of robotic rollators from the perspective of users

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Purpose: To evaluate the effectiveness and perception of robotic rollators (RRs) from the perspective of users. Methods: Studies identified in a previous systematic review published on 2016 on the methodology of studies evaluating RRs by the user perspective were re-screened for eligibility based on the following inclusion criteria: evaluation of the human–robot interaction from the user perspective, use of standardized outcome measurements, and quantitative presentation of study results. Results: Seventeen studies were eligible for inclusion. Due to the clinical and methodological heterogeneity across studies, a narrative synthesis of study results was conducted. We found conflicting results concerning the effectiveness of the robotic functionalities of the RRs. Only a few studies reported superior user performance or reduced physical demands with the RRs compared to unassisted conditions or conventional assistive mobility devices; however, without providing statistical evidence. The user perception of the RRs was found to be generally positive. Conclusions: There is still no sufficient evidence on the effectiveness of RRs from the user perspective. More well-designed, high-quality studies with adequate study populations, larger sample sizes, appropriate assessment strategies with outcomes specifically tailored to the robotic functionalities, and statistical analyses of results are required to evaluate RRs at a higher level of evidence.Implications for Rehabilitation RRs cover intelligent functionalities that focus on gait assistance, obstacle avoidance, navigation assistance, sit-to-stand transfer, body weight support or fall prevention. The evaluation from the user perspective is essential to ensure that RRs effectively address users’ needs, requirements and preferences. The evidence on the effectiveness of RRs is severely hampered by the low methodological quality of most of the available studies. RRs seem generally to be perceived as positive by the users. There is very limited evidence on the effectiveness and benefits of RRs compared to conventional assistive mobility devices. Further research with high methodological quality needs to be conducted to reach more robust conclusions about the effectiveness of RRs