AIMC Topic: Walking Speed
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Human Gait Entrainment to Soft Robotic Hip Perturbation During Simulated Overground Walking.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 24, 2024
Entraining human gait with a periodic mechanical perturbation has been proposed as a potentially effective strategy for gait rehabilitation, but the related studies have mostly depended on the use of a fixed-speed treadmill (FST) due to various pract...
Hybrid learning mechanisms under a neural control network for various walking speed generation of a quadruped robot.
Neural networks : the official journal of the International Neural Network Society
Aug 26, 2023
Legged robots that can instantly change motor patterns at different walking speeds are useful and can accomplish various tasks efficiently. However, state-of-the-art control methods either are difficult to develop or require long training times. In t...
Within- and between-therapist agreement on personalized parameters for robot-assisted gait therapy: the challenge of adjusting robotic assistance.
Journal of neuroengineering and rehabilitation
Jun 20, 2023
BACKGROUND: Stationary robotic gait trainers usually allow for adjustment of training parameters, including gait speed, body weight support and robotic assistance, to personalize therapy. Consequently, therapists personalize parameter settings to pur...
Effect of Gait Speed on Trajectory Prediction Using Deep Learning Models for Exoskeleton Applications.
Sensors (Basel, Switzerland)
Jun 18, 2023
Gait speed is an important biomechanical determinant of gait patterns, with joint kinematics being influenced by it. This study aims to explore the effectiveness of fully connected neural networks (FCNNs), with a potential application for exoskeleton...
Optimizing Representations of Multiple Simultaneous Attributes for Gait Generation Using Deep Learning.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 17, 2023
Rich variations in gait are generated according to several attributes of the individual and environment, such as age, athleticism, terrain, speed, personal "style", mood, etc. The effects of these attributes can be hard to quantify explicitly, but re...
Concurrent validity of artificial intelligence-based markerless motion capture for over-ground gait analysis: A study of spatiotemporal parameters.
Journal of biomechanics
Aug 30, 2022
Gait analysis is used in research and clinical environments; yet several limitations exist in current methodologies. Markerless systems, utilizing high-speed video and artificial intelligence, eliminate most limitations encountered in marker-, depth-...
Theory of Fast Walking With Human-Driven Load-Carrying Robot Exoskeletons.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 22, 2022
Reaching and maintaining high walking speeds is challenging for a human when carrying extra weight, such as walking with a heavy backpack. Robotic limbs can support a heavy backpack when standing still, but accelerating a backpack within a couple of ...
Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.
Journal of neuroengineering and rehabilitation
Apr 22, 2022
BACKGROUND: Lokomat therapy for gait rehabilitation has become increasingly popular. Most evidence suggests that Lokomat therapy is equally effective as but not superior to standard therapy approaches. One reason might be that the Lokomat parameters ...
Walking with robot-generated haptic forces in a virtual environment: a new approach to analyze lower limb coordination.
Journal of neuroengineering and rehabilitation
Sep 9, 2021
BACKGROUND: Walking with a haptic tensile force applied to the hand in a virtual environment (VE) can induce adaptation effects in both chronic stroke and non-stroke individuals. These effects are reflected in spatiotemporal outcomes such as gait spe...
XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes.
Scientific reports
Jun 9, 2021
This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63-89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and...
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