AIMC Topic: Walking
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Treatment with robot-assisted gait trainer Walkbot along with physiotherapy vs. isolated physiotherapy in children and adolescents with cerebral palsy. Experimental study.
BMC neurology
Jul 15, 2024
BACKGROUND: Improving walking ability is a key objective in the treatment of children and adolescents with cerebral palsy, since it directly affects their activity and participation. In recent years, robotic technology has been implemented in gait tr...
On the analysis and control of a bipedal legged locomotion model via partial feedback linearization.
Bioinspiration & biomimetics
Jul 9, 2024
In this study, we introduce a new model for bipedal locomotion that enhances the classical spring-loaded inverted pendulum (SLIP) model. Our proposed model incorporates a damping term in the leg spring, a linear actuator serially interconnected to th...
Evidence that robot-assisted gait training modulates neuroplasticity after stroke: An fMRI pilot study based on graph theory analysis.
Brain research
Jul 6, 2024
OBJECTIVES: To investigate alterations of whole-brain network after stroke and therapeutic mechanisms of robot-assisted gait training (RAGT).
A Residual U-Net Neural Network for Seismocardiogram Denoising and Analysis During Physical Activity.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Seismocardiogram (SCG) signals are noninvasively obtained cardiomechanical signals containing important features for cardiovascular health monitoring. However, these signals are prone to contamination by motion noise, which can significantly impact a...
Overground Gait Training With a Wearable Robot in Children With Cerebral Palsy: A Randomized Clinical Trial.
JAMA network open
Jul 1, 2024
IMPORTANCE: Cerebral palsy (CP) is the most common developmental motor disorder in children. Robot-assisted gait training (RAGT) using a wearable robot can provide intensive overground walking experience.
Research on Monitoring Assistive Devices for Rehabilitation of Movement Disorders through Multi-Sensor Analysis Combined with Deep Learning.
Sensors (Basel, Switzerland)
Jul 1, 2024
This study aims to integrate a convolutional neural network (CNN) and the Random Forest Model into a rehabilitation assessment device to provide a comprehensive gait analysis in the evaluation of movement disorders to help physicians evaluate rehabil...
Knee Angle Estimation from Surface EMG during Walking Using Attention-Based Deep Recurrent Neural Networks: Feasibility and Initial Demonstration in Cerebral Palsy.
Sensors (Basel, Switzerland)
Jun 28, 2024
Accurately estimating knee joint angle during walking from surface electromyography (sEMG) signals can enable more natural control of wearable robotics like exoskeletons. However, challenges exist due to variability across individuals and sessions. T...
EMG-based prediction of step direction for a better control of lower limb wearable devices.
Computer methods and programs in biomedicine
Jun 24, 2024
BACKGROUND AND OBJECTIVES: Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control...
Wearable Robot Design Optimization Using Closed-Form Human-Robot Dynamic Interaction Model.
Sensors (Basel, Switzerland)
Jun 23, 2024
Wearable robots are emerging as a viable and effective solution for assisting and enabling people who suffer from balance and mobility disorders. Virtual prototyping is a powerful tool to design robots, preventing the costly iterative physical protot...
Enhancing fall risk assessment: instrumenting vision with deep learning during walks.
Journal of neuroengineering and rehabilitation
Jun 22, 2024
BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking pro...
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