51,420 research outputs found
Rehabilitation robot cell for multimodal standing-up motion augmentation
The paper presents a robot cell for multimodal standing-up motion augmentation. The robot cell is aimed at augmenting the standing-up capabilities of impaired or paraplegic subjects. The setup incorporates the rehabilitation robot device, functional electrical stimulation system, measurement instrumentation and cognitive feedback system. For controlling the standing-up process a novel approach was developed integrating the voluntary activity of a person in the control scheme of the rehabilitation robot. The simulation results demonstrate the possibility of âpatient-drivenâ robot-assisted standing-up training. Moreover, to extend the system capabilities, the audio cognitive feedback is aimed to guide the subject throughout rising. For the feedback generation a granular synthesis method is utilized displaying high-dimensional, dynamic data. The principle of operation and example sonification in standing-up are presented. In this manner, by integrating the cognitive feedback and âpatient-drivenâ actuation systems, an effective motion augmentation system is proposed in which the motion coordination is under the voluntary control of the user
The ixiQuarks: merging code and GUI in one creative space
This paper reports on ixiQuarks; an environment of instruments and effects that is built on top of the audio programming language SuperCollider. The rationale of these instruments is to explore alternative ways of designing musical interaction in screen-based software, and investigate how semiotics in interface design affects the musical output. The ixiQuarks are part of external libraries available to SuperCollider through the Quarks system. They are software instruments based on a non- realist design ideology that rejects the simulation of acoustic instruments or music hardware and focuses on experimentation at the level of musical interaction. In this environment we try to merge the graphical with the textual in the same instruments, allowing the user to reprogram and change parts of them in runtime. After a short introduction to SuperCollider and the Quark system, we will describe the ixiQuarks and the philosophical basis of their design. We conclude by looking at how they can be seen as epistemic tools that influence the musician in a complex hermeneutic circle of interpretation and signification
Speech-driven Animation with Meaningful Behaviors
Conversational agents (CAs) play an important role in human computer
interaction. Creating believable movements for CAs is challenging, since the
movements have to be meaningful and natural, reflecting the coupling between
gestures and speech. Studies in the past have mainly relied on rule-based or
data-driven approaches. Rule-based methods focus on creating meaningful
behaviors conveying the underlying message, but the gestures cannot be easily
synchronized with speech. Data-driven approaches, especially speech-driven
models, can capture the relationship between speech and gestures. However, they
create behaviors disregarding the meaning of the message. This study proposes
to bridge the gap between these two approaches overcoming their limitations.
The approach builds a dynamic Bayesian network (DBN), where a discrete variable
is added to constrain the behaviors on the underlying constraint. The study
implements and evaluates the approach with two constraints: discourse functions
and prototypical behaviors. By constraining on the discourse functions (e.g.,
questions), the model learns the characteristic behaviors associated with a
given discourse class learning the rules from the data. By constraining on
prototypical behaviors (e.g., head nods), the approach can be embedded in a
rule-based system as a behavior realizer creating trajectories that are timely
synchronized with speech. The study proposes a DBN structure and a training
approach that (1) models the cause-effect relationship between the constraint
and the gestures, (2) initializes the state configuration models increasing the
range of the generated behaviors, and (3) captures the differences in the
behaviors across constraints by enforcing sparse transitions between shared and
exclusive states per constraint. Objective and subjective evaluations
demonstrate the benefits of the proposed approach over an unconstrained model.Comment: 13 pages, 12 figures, 5 table
On sparsity averaging
Recent developments in Carrillo et al. (2012) and Carrillo et al. (2013)
introduced a novel regularization method for compressive imaging in the context
of compressed sensing with coherent redundant dictionaries. The approach relies
on the observation that natural images exhibit strong average sparsity over
multiple coherent frames. The associated reconstruction algorithm, based on an
analysis prior and a reweighted scheme, is dubbed Sparsity Averaging
Reweighted Analysis (SARA). We review these advances and extend associated
simulations establishing the superiority of SARA to regularization methods
based on sparsity in a single frame, for a generic spread spectrum acquisition
and for a Fourier acquisition of particular interest in radio astronomy.Comment: 4 pages, 3 figures, Proceedings of 10th International Conference on
Sampling Theory and Applications (SampTA), Code available at
https://github.com/basp-group/sopt, Full journal letter available at
http://arxiv.org/abs/arXiv:1208.233
Granular synthesis for display of time-varying probability densities
We present a method for displaying time-varying probabilistic information to users using an asynchronous granular synthesis technique. We extend the basic synthesis technique to include distribution over waveform source, spatial position, pitch and time inside waveforms. To enhance the synthesis in interactive contexts, we "quicken" the display by integrating predictions of user behaviour into the sonification. This includes summing the derivatives of the distribution during exploration of static densities, and using Monte-Carlo sampling to predict future user states in nonlinear dynamic systems. These techniques can be used to improve user performance in continuous control systems and in the interactive exploration of high dimensional spaces. This technique provides feedback from users potential goals, and their progress toward achieving them; modulating the feedback with quickening can help shape the users actions toward achieving these goals. We have applied these techniques to
a simple nonlinear control problem as well as to the sonification of on-line probabilistic gesture recognition. We are applying these displays to mobile, gestural interfaces, where visual display is often impractical. The granular synthesis approach is theoretically elegant and easily applied in contexts where dynamic probabilistic displays are required
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