AIMC Topic: Movement

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A New Approach on HCI Extracting Conscious Jaw Movements Based on EEG Signals Using Machine Learnings.

Journal of medical systems
Machine computer interfaces (MCI) are assistive technologies enabling paralyzed peoples to control and communicate their environments. This study aims to discover and represents a new approach on MCI using left/right motions of voluntary jaw movement...

Bioinspired 3D Printable Soft Vacuum Actuators for Locomotion Robots, Grippers and Artificial Muscles.

Soft robotics
Continued technological progress in robotic systems has led to more applications where robots and humans operate in close proximity and even physical contact in some cases. Soft robots, which are made of highly compliant and deformable materials, pro...

A Neuromuscular Interface for Robotic Devices Control.

Computational and mathematical methods in medicine
A neuromuscular interface (NI) that can be employed to operate external robotic devices (RD), including commercial ones, was proposed. Multichannel electromyographic (EMG) signal is used in the control loop. Control signal can also be supplemented wi...

Assessing Wrist Movement With Robotic Devices.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. Complementing this application, exoskeletons can augment traditional ...

EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces.

Journal of neural engineering
OBJECTIVE: Brain-computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given...

Impact of Sliding Window Length in Indoor Human Motion Modes and Pose Pattern Recognition Based on Smartphone Sensors.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applie...

A study on plant root apex morphology as a model for soft robots moving in soil.

PloS one
Plants use many strategies to move efficiently in soil, such as growth from the tip, tropic movements, and morphological changes. In this paper, we propose a method to translate morphological features of Zea mays roots into a new design of soft robot...

Reshaping Movement Distributions With Limit-Push Robotic Training.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
High-cost situations need to be avoided. However, occasionally, cost may only be learned by experience. Here, we tested whether an artificially induced unstable and invisible high-cost region, a "limit-push" force field, might reshape people's motion...

Muscleless motor synergies and actions without movements: From motor neuroscience to cognitive robotics.

Physics of life reviews
Emerging trends in neurosciences are providing converging evidence that cortical networks in predominantly motor areas are activated in several contexts related to 'action' that do not cause any overt movement. Indeed for any complex body, human or e...

Human Activity Recognition from Body Sensor Data using Deep Learning.

Journal of medical systems
In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring...