AIMC Topic: Movement

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Droplets As Liquid Robots.

Artificial life
Liquid droplets are very simple objects present in our everyday life. They are extremely important for many natural phenomena as well as for a broad variety of industrial processes. The conventional research areas in which the droplets are studied in...

The effectiveness of robotic training depends on motor task characteristics.

Experimental brain research
Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies....

From biokinematics to a robotic active vision system.

Bioinspiration & biomimetics
Barn owls move their heads in very particular motions, compensating for the quasi-immovability of their eyes. These efficient predators often perform peering side-to-side head motions when scanning their surroundings and seeking prey. In this work, w...

Deep Manifold Learning Combined With Convolutional Neural Networks for Action Recognition.

IEEE transactions on neural networks and learning systems
Learning deep representations have been applied in action recognition widely. However, there have been a few investigations on how to utilize the structural manifold information among different action videos to enhance the recognition accuracy and ef...

Combining Upper Limb Robotic Rehabilitation with Other Therapeutic Approaches after Stroke: Current Status, Rationale, and Challenges.

BioMed research international
A better understanding of the neural substrates that underlie motor recovery after stroke has led to the development of innovative rehabilitation strategies and tools that incorporate key elements of motor skill relearning, that is, intensive motor t...

A robotic system for delivering novel real-time, movement dependent perturbations.

Gait & posture
Perturbations are often used to study movement control and balance, especially in the context of falling. Most often, discrete perturbations defined prior to the experiment are used to mimic external disturbances to balance. However, the largest prop...

Discriminatively Trained Latent Ordinal Model for Video Classification.

IEEE transactions on pattern analysis and machine intelligence
We address the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminative sub-events (e.g., onset a...

Effect of feedback from a socially interactive humanoid robot on reaching kinematics in children with and without cerebral palsy: A pilot study.

Developmental neurorehabilitation
PURPOSE: To examine whether children with or without cerebral palsy (CP) would follow a humanoid robot's (i.e., Darwin) feedback to move their arm faster when playing virtual reality (VR) games.

Applying machine learning to identify autistic adults using imitation: An exploratory study.

PloS one
Autism spectrum condition (ASC) is primarily diagnosed by behavioural symptoms including social, sensory and motor aspects. Although stereotyped, repetitive motor movements are considered during diagnosis, quantitative measures that identify kinemati...

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual ...