Recovery model

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Related publications (30)

Brain-Controlled Neuroprosthetic Therapies And Mechanisms Of Recovery After Spinal Cord Injury

Spinal cord injury (SCI) is the second leading cause of paralysis, which induces abrupt impairments with devastating consequences for the quality of life of patients. Despite significant progress in SCI treatment through neurorehabilitation training and sp ...

EPFL2017

Limits on Support Recovery with Probabilistic Models: An Information-Theoretic Framework

Volkan Cevher, Jonathan Mark Scarlett

The support recovery problem consists of deter- mining a sparse subset of a set of variables that is relevant in generating a set of observations, and arises in a diverse range of settings such as group testing, compressive sensing, and subset selection in ...

2015

Mutual Modelling in Robotics: Inspirations for the Next Steps

Pierre Dillenbourg, Séverin Lemaignan

Mutual modelling, the reciprocal ability to establish a mental model of the other, plays a fundamental role in human interactions. This complex cognitive skill is however difficult to fully apprehend as it encompasses multiple neuronal, psychological and s ...

2015

Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery

Roger Gassert, Maria Laura Blefari

Motor imagery (MI) has shown effectiveness in enhancing motor performance. This may be due to the common neural mechanisms underlying MI and motor execution (ME). The main region of the ME network, the primary motor cortex (M1), has been consistently linke ...

Frontiers Research Foundation2015

Muscle Spindle Feedback Directs Locomotor Recovery and Circuit Reorganization after Spinal Cord Injury

Grégoire Courtine, Isabel Laura Vollenweider

Spinal cord injuries alter motor function by disconnecting neural circuits above and below the lesion, rendering sensory inputs a primary source of direct external drive to neuronal networks caudal to the injury. Here, we studied mice lacking functional mu ...

Elsevier2014

Lorentzian Iterative Hard Thresholding: Robust Compressed Sensing With Prior Information

Rafael Eduardo Carrillo Rangel

Commonly employed reconstruction algorithms in compressed sensing (CS) use the L-2 norm as the metric for the residual error. However, it is well-known that least squares (LS) based estimators are highly sensitive to outliers present in the measurement vec ...

Institute of Electrical and Electronics Engineers2013

Thresholding-based reconstruction of compressed correlated signals

Pascal Frossard, Alhussein Fawzi, Tamara Tosic

We consider the problem of recovering a set of correlated signals (\emph{e.g.,} images from different viewpoints) from a few linear measurements per signal. We assume that each sensor in a network acquires a compressed signal in the form of linear measurem ...

2012

Isothermal recovery rates in shape memory polyurethanes

John Christopher Plummer, Charly David Azra

This work compares the time dependence of isothermal shape recovery in thermoset and thermoplastic shape memory polyurethanes (SMPUs) with comparable glass transition temperatures. In each case, tensile tests have been used to quantify the influence of var ...

2011

Atomic boxes: coordinated exception handling with transactional memory

Vincent Gramoli, Pascal Felber

In concurrent programs raising an exception in one thread does not prevent others from operating on an inconsistent shared state. Instead, exceptions should ideally be handled in coordination by all the threads that are affected by their cause. In this pap ...

2011

Problem Structuring Methods in System Dynamics Modeling-A Cognitive Fit Perspective

Alain Wegmann, Arash Golnam, Gorica Tapandjieva Sekulovska, Sérgio Viana

The knowledge residing in the mental models of clients and stakeholders is considered as a crucial source of information by system dynamicists. Despite the importance of this knowledge, the theory of SD does not provide practical means for eliciting and re ...

2011

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