AIMC Topic: Walking

Clear Filters Showing 301 to 310 of 774 articles

The Impact of Load Style Variation on Gait Recognition Based on sEMG Images Using a Convolutional Neural Network.

Sensors (Basel, Switzerland)
Surface electromyogram (sEMG) signals are widely employed as a neural control source for lower-limb exoskeletons, in which gait recognition based on sEMG is particularly important. Many scholars have taken measures to improve the accuracy of gait rec...

The Effects of Over-Ground Robot-Assisted Gait Training for Children with Ataxic Cerebral Palsy: A Case Report.

Sensors (Basel, Switzerland)
Poor balance and ataxic gait are major impediments to independent living in ataxic cerebral palsy (CP). Robot assisted-gait training (RAGT) has been shown to improve the postural balance and gait function in children with CP. However, there is no rep...

Locomotion Control With Frequency and Motor Pattern Adaptations.

Frontiers in neural circuits
Existing adaptive locomotion control mechanisms for legged robots are usually aimed at one specific type of adaptation and rarely combined with others. Adaptive mechanisms thus stay at a conceptual level without their coupling effect with other mecha...

Different Effects of Robot-Assisted Gait and Independent Over-Ground Gait on Foot Plantar Pressure in Incomplete Spinal Cord Injury: A Preliminary Study.

International journal of environmental research and public health
BACKGROUND: There is insufficient evidence to establish the optimal treatment protocol for robot-assisted gait training.

A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors.

Sensors (Basel, Switzerland)
Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laborator...

From a biological template model to gait assistance with an exosuit.

Bioinspiration & biomimetics
The invention of soft wearable assistive devices, known as exosuits, introduced a new aspect in assisting unimpaired subjects. In this study, we designed and developed an exosuit with compliant biarticular thigh actuators called BATEX. Unlike the con...

Synergy-Based Neural Interface for Human Gait Tracking With Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neural information decomposed from electromyography (EMG) signals provides a new path of EMG-based human-machine interface. Instead of the motor unit decomposition-based method, this work presents a novel neural interface for human gait tracking base...

Effect of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents using deep learning.

Traffic injury prevention
OBJECTIVE: The aim of this study is to identify the effects of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents via deep learning.

Walking-induced exposure of biological particles simulated by a children robot with different shoes on public floors.

Environment international
Inhalation exposure to the resuspended biological particles from public places can cause adverse effects on human health. In this work, carpet dust samples were first collected from twenty example conference and hotel rooms by a vacuum cleaner. A bip...

ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments.

Sensors (Basel, Switzerland)
Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multip...