Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems. However, in most cases...
Interaction control plays an important role in rehabilitation devices to ensure training safety and efficacy. Compliance adaptation of interaction is vital for enabling robot movements to better suit the patient's requirements as human joint characte...
We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networks (RBF) and linear models (LM) accuracy to predict the centre of mass (CM) horizontal speed at low-moderate, heavy and severe swimming intensities us...
Field-based sprint performance assessments rely on metrics derived from a simple model of sprinting dynamics parameterized by 2 constants, v and τ, which indicate a sprinter's maximal theoretical velocity and the time it takes to approach v, respecti...
The goal of this study was to develop and validate a non-invasive approach to estimate scapular kinematics in individual patients. We hypothesized that machine learning algorithms could be developed using motion capture data to accurately estimate dy...
We report on the development and analysis of a new torque-actuated dissipative spring loaded inverted pendulum model with rolling contact (TDR-SLIP), which is a successor to the previously developed spring loaded inverted pendulum model with rolling ...
Annotation of foot-contact and foot-off events is the initial step in post-processing for most quantitative gait analysis workflows. If clean force plate strikes are present, the events can be automatically detected. Otherwise, annotation of gait eve...
Many fish generate thrust by undulating one or multiple elongated fins while keeping their body straight. This propulsion mechanism has stimulated interest in both biology and bio-inspired marine propulsion because its maneuverability and efficiency ...
OBJECTIVE: To evaluate the differences between walking on an advanced robotic locomotion interface called the Treadport and walking overground with healthy subjects.
IEEE transactions on bio-medical engineering
Jan 10, 2019
Continuous human motion intent learning may be modeled using a Gaussian process (GP) autoregression based evolving system to cope with the unspecified and time-varying motion patterns. Electromyography (EMG) signals are the primary input. GP is used ...
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