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Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost.

Spinal cord injury (SCI) causes both lower limb motor dysfunction and associated neuropathic pain. Although these two conditions share related cortical mechanisms, different interventions are currently used to treat each condition. With intensive training using entertaining virtual reality (VR) scenarios, it may be possible to reshape cortical networks thereby reducing neuropathic pain and improving motor function. We have created the first VR training system combining action observation and execution addressing lower limb function in incomplete SCI (iSCI) patients. A particular feature of the system is the use of size-adjustable shoes with integrated motion sensors. A pilot single-case clinical study is currently being conducted on six iSCI patients. Two patients tested to date were highly motivated to perform and reported improved physical well-being. They improved in playing skill and in controlling the virtual lower limbs. There were post-intervention indications of neuropathic pain decrease, muscle strength increase, faster walking speed and improved performance on items relevant for ambulation. In addition functional MRI before and after treatment revealed a decreased activation pattern. We interpret this result as an improvement of neuronal synergies for this task. These results suggest that our VR system may be beneficial for both reducing neuropathic pain and improving motor function in iSCI patients.

Compliant actuation contributes enormously in legged locomotion robotics since it is able to alleviate control efforts in improving the robot’s adaptability and energy efficiency. In this paper, we present a novel design of a variable stiffness rotary actuator, called MESTRAN, which was especially targeted to address the limitations in terms of the amount of energy and time required to vary the stiffness of an actuated joint. We have constructed a mechanical model in simulation and a physical prototype. We conducted a series of experiments to validate the performance of the MESTRAN actuator prototype. The results from the simulation and experiments show that MESTRAN allows independent control of stiffness and position of an actuated rotary joint with a large operational range and high speed. The torque-displacement relationship is close to linear. Lastly, the MESTRAN actuator is energy-efficient since a certain stiffness level is maintained without energy input.

Technology assisted therapy has the potential to transform rehabilitation options available, and to dramatically increase the reach of today's healthcare system. Yet challenges persist in rendering translational application designs that optimize the full potential of technology and create value for the patient and the therapist. In a step towards optimizing value of technologies for practical applications to support very weak patients who might otherwise be unable to participate in traditional therapies, an integrated sensory motor training station was designed and developed. Inspired by recent neuroscientific research findings the goal of the design was to provide concurrent first person perspective immersive action observation of both virtual and real elements for motor and sensory experience; the system incorporates a virtual limb proxy that can be personalized and actuated by the robot and that is accompanied by exercise practice in peripersonal space for a plasticity promoting experience for the hand and arm. The station uses virtual reality and real objects for visual sensory experience, real objects also provide tactile sensory experience, and an exoskeleton upper limb robot provides assistance to patients. For many patients, successful movement and movement intensity required in rehabilitation is not achievable without the robot assistance. The multi-sensory features of the system promote a top-down strategy for training the upper limb (hand and arm) complementing the robot training; the system is ideally targeted for weak patients and those with tactile or proprioception sensory loss and those who are known to benefit from multi-sensory experiences.

It has been a quite while since people realized that self-assembly technique may be a strong method to manufacture 3D micro products. In this contribution, we investigate some major concerns about realizing such a small sized robot. First we introduce the concept of self-assembly and introduce examples both from nature and artificial products. Followed by the main problems in self-assembly which can be seen in various scales, we classify them into four groups - (A) assembly constraint issues, (B) stochastic motion issues, (C) interactions on physical property issues, and (D) engineering issues. Then we show a segregation effect with our developed platform as an example of self-organizing behavior achieved in a distributed manner.

In recent years, the public and the private spheres have been blended in interesting ways. The mass media make the most private aspects of the lives of celebrities public and also the lives of ordinary people regularly feature in their publications. Letters to the editor (and more recently online commentaries) have always been a format for ordinary people to make their private voices heard in public. However, on the basis of data from The Times published in 1985 and from the Times Online published in 2008, we argue that in the development from the letters to the editor to the online discussion forums new configurations of public and private are discernible. This development affects the communicative situation, the content and the linguistic realization of the texts in different, albeit not independent ways. For the purpose of this argument it is necessary to develop a new communicative model that clearly distinguishes between the relevant dimensions of public and private. Koch and Oesterreicher (e.g. in Koch and Oesterreicher 1985) developed a model of communication that relates the communicative situation to strategies of linguistic realization and distinguishes consistently between the phonic and graphic realization of language on the one hand, and between the language of immediacy and the language of distance on the other. This model will serve as the backdrop for our own model. We propose that their dimension of immediacy versus distance needs to be separated into three different dimensions. We, therefore, distinguish systematically between the communicative situation (the scale of public accessibility), the content (the scale of privacy) and the linguistic realization (the scale of linguistic immediacy). On the basis of this model it is possible to describe the traditional letters to the editor as being characterized by non-private contents and the language of distance while the discussion sections of recent online newspapers are characterized by private contents and the language of immediacy.

This article gives a unified semantic analysis of the various uses of the Dutch discourse marker eigenlijk. Eigenlijk is analyzed as involving implicit assumptions of the speaker about the hearer's expectations: by using eigenlijk, the speaker marks the plausibility of what s/he assumes the hearer to infer on the basis of their shared beliefs. Hence, the speaker not only recognizes the discrepancy between the speaker's and the hearer's perspective, but in addition, the speaker puts him/herself in the hearer's shoes. The claims are empirically supported by the results of a web experiment as well as by data from natural language.

Research in multimodal motor learning in sports is highly demanding with respect to the equipment, especially when the same equipment has to be reconfigured for different applications. In our multimodal motion synthesis lab (M3-lab) we apply visual, auditory, and haptic displays as well as feedback to enhance human motor learning. The demands on our haptic display, a tendon-based parallel robot (TBPR), are particularly high: a large workspace needs to be covered, the robotic device must be versatile, the visual and auditory modality should not be affected, high velocities and forces have to be realizable to render different sports applications, and user-cooperative control strategies should be applicable.

This paper presents the design and control of an actuated bivalve robot, which has been developed to study the burrowing locomotion of bivalves in sediment. The setup consists of a tank filled with sand and water, plastic models of bivalve shells capable of expelling water and an external actuation mechanism simulating the rocking burrowing motion typically used by these animals. The realistic shell shapes have been realized using three-dimensional plotting techniques allowing testing influences of different shell shapes and surface structures (sculptures) on the burrowing efficiency. Based on the experimental setup, the burrowing process has been reproduced. The results show that this setup can be used to identify correlations in the burrowing process. Further experimental work will investigate the influence of factors such as shell shape and sculpture or the motion sequence on the burrowing performance.

How is our body imprinted in our brain? This seemingly simple question is a subject of investigations of diverse disciplines, psychology, and philosophy originally complemented by neurosciences more recently. Despite substantial efforts, the mysteries of body representations are far from uncovered. The most widely used notions-body image and body schema-are still waiting to be clearly defined. The mechanisms that underlie body representations are coresponsible for the admiring capabilities that humans or many mammals can display: combining information from multiple sensory modalities, controlling their complex bodies, adapting to growth, failures, or using tools. These features are also desirable in robots. This paper surveys the body representations in biology from a functional or computational perspective to set ground for a review of the concept of body schema in robotics. First, we examine application-oriented research: how a robot can improve its capabilities by being able to automatically synthesize, extend, or adapt a model of its body. Second, we summarize the research area in which robots are used as tools to verify hypotheses on the mechanisms underlying biological body representations. We identify trends in these research areas and propose future research directions.

The human hand is one of the most complex structures in the body, being involved in dexterous manipulation and fine sensing. Traditional engineering approaches have mostly attempted to match such complexity in robotics without sufficiently stressing on the underlying mechanisms that its morphology encodes. In this work, we propose an artificial skin able to encode, through its morphology, the tactile sense of a robotic hand, characteristic to slippage events. The underlying layout consists of ridges and allows slippage detection and the quantification of slippage speed. Such encoding of slippage signal becomes suitable for relaying tactile feedback to users in prosthetic applications. This approach emphasizes the importance of exploiting morphology and mechanics in structures for the design of prosthetic interfaces.

The identification of jittered regular signals (="patterns#) embedded in a noisy background is an important and difficult task, particularly in the neurosciences. Traditional methods generally fail to capture such signals. Staircase-like structures in the log–log correlation plot, however, are reliable indicators of such signal components.We provide a number of applications of this method and derive an analytic relationship between the length of the pattern n and the maximal number of steps s(n,m) that are observable at a chosen embedding dimension m. For integer linearly independent patterns and small jitter and noise, the length of the embedded pattern can be calculated from the number of steps. The method is demonstrated to have a huge potential for experimental applications.

This paper presents the design of a new user-cooperative rope robot. This robot serves as a large-scale haptic interface in a multi-modal Cave environment used for sport simulation. In contrast to current rope robots, the configuration of the presented robot is adaptable to different simulation tasks what makes the robot more versatile. However, this adaptability and the high dynamics in sports lead to challenging requirements and specific design criteria of the hardware components. We present the requirements on the single robot components as well as the design of the entire setup optimized in terms of user-cooperativity and versatility. The setup includes sensors to measure the relevant parameters for user-cooperative control, i.e. position with a high resolution and the rope forces. Furthermore, an algorithm is introduced, which calculates the distance between the single ropes and the user in order to avoid collisions between the ropes and the user. Single points on the user's body are, therefore, tracked with a motion tracking system; the user's single body parts are then represented by geometrical objects whose distances to the ropes are calculated. The algorithm is programmed in such way that the collision detection runs in real-time. Both, the hardware and the algorithm, were evaluated experimentally in two applications, a rowing simulator and a tennis application. The hardware concept combined with the distance calculation allows the use of new kinematic concepts and expands the spectrum of realizable movement tasks that can be implemented into the Cave environment.

For haptic devices, compensation of the robot's gravity is a frequent strategy with the aim to reduce interaction forces between robot and human in zero-impedance control. However, a closer look at the composition of these interaction forces may reveal that the net effect of uncompensated gravitational components of the robot actually reduces interaction forces during dynamic movements, because inertial and gravitational components at least partially compensate each other. This is the case in lower extremity exoskeletons, where less user force is necessary to swing the robot's leg when gravity helps. Here, we go one step further by shaping optimal passive dynamics for arbitrary haptic devices. The proposed method of Generalized Elasticies uses conservative force fields to improve haptic transparency for certain movements types. In an example realization, these force fields are generated by elasticities spanning multiple joints. Practical experiments with the Lokomat lower extremity exoskeleton show the success of the proposed method in terms of reduced interaction torques and more physiological user motion compared to gravity compensation.

We introduce an explorative tool for affect analysis from texts. Rather than the full range of emotions, feelings, and sentiment, our system is currently restricted to the positive or negative polarity of phrases and sentences. It analyses the input texts with the aid of a affect lexicon that specifies among others the prior polarity (positive or negative) of words. A chunker is used to determine phrases that are the basis for a compositional treatment of phraselevel polarity assignment. In our current experiments we focus on phrases that are targeted towards persons, be it the writer (I, my, me,.), the social group including the writer (we, our,.) or the reader (you, your,). We evaluate our system with standard data (customer reviews). We also give initial results from a small corpus of 35 texts taken from a panel group called 'I battle depression'.

The article presents a mathematical model of short-term recognition based on dual-process models and the three- component theory of working memory [Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 411-421]. Familiarity arises from activated representations in long-term memory, ignoring their relations; recollection retrieves bindings in the capacity- limited component of working memory. In three experiments participants encoded two short lists of nonwords for immediate recognition, one of which was then cued as irrelevant. Probes from the irrelevant list were rejected more slowly than new probes; this was also found with probes recombining letters of irrelevant nonwords, suggesting that familiarity arises from individual letters independent of their relations. When asked to accept probes whose letters were all in the relevant list, regardless of their conjunction, participants accepted probes preserving the original conjunctions faster than recombinations, showing that recollection accessed feature bindings automatically. The model fit the data best when familiarity depended only on matching letters, whereas recollection used binding information.

We present an incremental and unsupervised face recognition system and evaluate it offline using data which were automatically collected by Mertz, a robotic platform embedded in real human environment. In an eight-day-long experiment, the robot autonomously detects, tracks, and segments face images during spontaneous interactions with over 500 passersby in public spaces and automatically generates a data set of over 100,000 face images. We describe and evaluate a novel face clustering algorithm using these data (without any manual processing) and also on an existing face recognition database. The face clustering algorithm yields good and robust performance despite the extremely noisy data segmented from the realistic and difficult public environment. In an incremental recognition scheme evaluation, the system is correct 74% of the time when it declares “I don't know this person” and 75.1% of the time when it declares “I know this person, he/she is …” The latter accuracy improves to 83.8% if the system is allowed some learning curve delay in the beginning.

International audience; Pattern generators found in the spinal cord are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics giving to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitutes an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body's dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment). Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cord, and for exploring the motor synergies in robots.

We present a novel type of inter-module connection mechanism for waterborne modular robotic systems. The proposed mechanism exploits the thermoelectric effect to cool down and freeze the water between two modules thus causes them to attach to each other. We validate the feasibility of this mechanism by embedding a Peltier heat pump (m = 0.8 g) in two types of cm scale self-assembly systems, one in which the modules are free to move and one in which the modules are linked together by hinges. Our experimental results demonstrate that the proposed Peltier-based connector has (a) a high bond strength/weight ratio for a rather large range of temperatures and (b) is rather robust against misalignments between docking modules, making it a useful alternative to current connection mechanisms for small scale low autonomy self-assembly systems.

We present a novel type of inter-module connection mechanism for waterborne modular robotic systems. The proposed mechanism exploits the thermoelectric effect to cool down and freeze the water between two modules thus causes them to attach to each other. We validate the feasibility of this mechanism by embedding Peltier heat pumps (m = 0.8 g) in a cm scale self-assembly system. Our experimental results demonstrate that the proposed Peltier-based connector has (a) a high bond strength/weight ratio for a rather large range of temperatures and (b) is rather robust against misalignments between docking modules, making it a useful alternative to current connection mechanisms for small scale low autonomy self-assembly systems.

Modular robots are mechatronic systems that can rearrange their connectivity to create new topologies to accomplish diverse tasks. In previous work, we have studied a modular reconfigurable robot (Slimebot) characterized by a spontaneous inter-module connection control mechanism. The modules of Slimebot connect to each other via a functional material which satisfies physical coupling between the ones. Here, we investigate the effect of heterogeneous inter-module coupling strengths on the adaptivity of Slimebot (here measured in terms of structural stability and locomotive speed). Simulation results show that a certain amount of heterogeneity improves the adaptivity of the system compared to the case of homogeneous modules. The only assumption that needs to be satisfied by the system with heterogeneous couplings is compliance to Steinberg's energy minimization theory.

Self-assembly is a process through which an organized structure can spontaneously form from simple parts. Taking inspiration from biological examples of self-assembly, we designed and built a water-based modular robotic system consisting of autonomous plastic tiles capable of aggregation on the surface of water. In this paper, we investigate the effect of the morphology (here: shape) of the tiles on the yield of the self-assembly process, that is, on the final amount of the desired aggregate. We describe experiments done with the real system as well as with a computer simulation thereof. We also present results of a mathematical analysis of the modular system based on chemical rate equations which point to a power-law relationship between yield rate and shape. Using the real system, we further demonstrate how through a single parameter (here: the externally applied electric potential) it is possible to control the self-assembly of propeller-like aggregates. Our results seem to provide a starting point (a) for quantifying the effect of morphology on the yield rates of self- assembly processes and (b) for assessing the level of modular autonomy and computational resources required for emergent functionality to arise.

A critical step in the product generation of satellite or airborne earth observation data is the correction of atmospheric features. Due to the complexity of the underlying physical model and the amount of coordinated effort required to provide, verify and maintain baseline atmospheric observations, one particular scientific modelling program, modtran, whose ancestor was first released in 1972, has become a de facto basis for such processing. While this provides the basis of per-pixel physical modelling, higher-level algorithms, which rely on the output of potentially thousands of runs of modtran are required for the processing of an entire scene. The widely-used atcor family of atmospheric correction software employs the commonly-used strategy of pre-computing a large look up table (lut) of values, representing modtran input parameter variation in multiple dimensions, to allow for reasonable running times in operation. The computation of this pre-computed look up table has previously taken weeks to produce a dvd (about 4 GB) of output. The motivation for quicker turnaround was introduced when researchers at multiple institutions began collaboration on extending atcor features into more specialized applications. In this setting, a parallel implementation is investigated with the primary goals of: the parallel execution of multiple instances of modtran as opaque third-party software, the consistency of numeric results in a heterogeneous compute environment, the potential to make use of otherwise idle computing resources available to researchers located at multiple institutions, and acceptable total turnaround time. In both grid and cluster environments, parallel generation of a numerically consistent lut is shown to be possible and reduce ten days of computation time on a single, high-end processor to under two days of processing time with as little as eight commodity CPUs. Runs on up to 64 processors are investigated and the advantages and disadvantages of clusters and grids are briefly explored in reference to the their evaluation in a medium-sized collaborative project.

Proceedings of Virtual Rehabilitation 2008, ISBN:978-1-4244-2700-0, ISBN:978-1-4244-2701-7

Paediatric rehabilitation using virtual reality systems pose unique usability challenges distinct from those in adult rehabilitation. These challenges relate to the different epidemiology and aetiology of childrenpsilas disorders requiring rehabilitation and the physical design of interactive virtual reality hardware for children of varying sizes. Just as importantly, children need highly entertaining interactive scenarios that suit their differing levels of cognitive development and thus their differing abilities to comprehend gaming scenarios. In this paper we present our virtual reality-based Paediatric Interactive Therapy System (PITS) designed specifically for upper arm rehabilitation in children aged from five years of age upwards. It incorporates a range of interchangeable position sensing devices (compass, bend sensor, pressure sensor and camera tracking) that can be adjusted to a large range of different hand sizes, and interactive gaming scenarios specifically designed for maximum entertainment value for children. We describe the neuroscientific principles behind our system, the technical details of the hardware components and the design of the interactive scenarios. An initial usability and patient acceptance pilot study has been conducted at the Rehabilitation Centre Affoltern of the University Childrenpsilas Hospital Zurich. To date all patients have accepted the system, and trained in reaching and grasping tasks at a far higher rate than in conventional occupational therapy. The system thus promises to be a valuable complement to conventional therapeutic programs offered in rehabilitation clinics.

As man-made systems become more complex and autonomous, there is a growing need for novel engineering methods that offer self-construction, adaptation to the environment, and self-repair. In a step towards developing such methods, we demonstrate how a simple model multicellular organism can assemble itself by replication from a single cell and finally express a fundamental behavior: foraging. Previous studies have employed evolutionary approaches to this problem. Instead, we aim at explicit design of self-constructing and -repairing systems by hierarchical specification of elementary intracellular mechanisms via a kind of genetic code. The interplay between individual cells and the gradually increasing self-created complexity of the local structure that surrounds them causes the serial unfolding of the final functional organism. The developed structure continuously feeds back to the development process, and so the system is also capable of self-repair.