AIMC Topic: Adaptation, Physiological
Clear Filters Showing 91 to 100 of 119 articles
Context-dependent coding and gain control in the auditory system of crickets.
The European journal of neuroscience
Aug 8, 2015
Sensory systems process stimuli that greatly vary in intensity and complexity. To maintain efficient information transmission, neural systems need to adjust their properties to these different sensory contexts, yielding adaptive or stimulus-dependent...
An experimental comparison of the relative benefits of work and torque assistance in ankle exoskeletons.
Journal of applied physiology (Bethesda, Md. : 1985)
Jul 9, 2015
Techniques proposed for assisting locomotion with exoskeletons have often included a combination of active work input and passive torque support, but the physiological effects of different assistance techniques remain unclear. We performed an experim...
Locomotor Adaptation by Transtibial Amputees Walking With an Experimental Powered Prosthesis Under Continuous Myoelectric Control.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 4, 2015
Lower limb amputees can use electrical activity from their residual muscles for myoelectric control of a powered prosthesis. The most common approach for myoelectric control is a finite state controller that identifies behavioral states and discrete ...
Variable Cadence Walking and Ground Adaptive Standing With a Powered Ankle Prosthesis.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 30, 2015
This paper describes a control approach that provides walking and standing functionality for a powered ankle prosthesis, and demonstrates the efficacy of the approach in experiments with a unilateral transtibial amputee subject. Both controllers inco...
Goal-directed multimodal locomotion through coupling between mechanical and attractor selection dynamics.
Bioinspiration & biomimetics
Mar 26, 2015
One of the most significant challenges in bio-inspired robotics is how to realize and take advantage of multimodal locomotion, which may help robots perform a variety of tasks adaptively in different environments. In order to address the challenge pr...
Adaptive control of uncertain nonaffine nonlinear systems with input saturation using neural networks.
IEEE transactions on neural networks and learning systems
Dec 19, 2014
This paper presents a tracking control methodology for a class of uncertain nonlinear systems subject to input saturation constraint and external disturbances. Unlike most previous approaches on saturated systems, which assumed affine nonlinear syste...
Uphill walking with a simple exoskeleton: plantarflexion assistance leads to proximal adaptations.
Gait & posture
Oct 23, 2014
While level walking with a pneumatic ankle-foot exoskeleton is studied extensively, less is known on uphill walking. The goals of this study were to get a better understanding of the biomechanical adaptations and the influence of actuation timing on ...
Adaptive neural control of nonlinear MIMO systems with time-varying output constraints.
IEEE transactions on neural networks and learning systems
Jul 15, 2014
In this paper, adaptive neural control is investigated for a class of unknown multiple-input multiple-output nonlinear systems with time-varying asymmetric output constraints. To ensure constraint satisfaction, we employ a system transformation techn...
Dynamics of Continuous Attractor Neural Networks With Spike Frequency Adaptation.
Neural computation
May 14, 2025
Attractor neural networks consider that neural information is stored as stationary states of a dynamical system formed by a large number of interconnected neurons. The attractor property empowers a neural system to encode information robustly, but it...
Deep learning insights into distinct patterns of polygenic adaptation across human populations.
Nucleic acids research
Dec 11, 2024
Response to spatiotemporal variation in selection gradients resulted in signatures of polygenic adaptation in human genomes. We introduce RAISING, a two-stage deep learning framework that optimizes neural network architecture through hyperparameter t...
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