AIMC Topic: Biomechanical Phenomena
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Accurate fall risk classification in elderly using one gait cycle data and machine learning.
Clinical biomechanics (Bristol, Avon)
May 8, 2024
BACKGROUND: Falls among the elderly are a major societal problem. While observations of medium-distance walking using inertial sensors identified potential fall predictors, classifying individuals at risk based on single gait cycles remains elusive. ...
A toe-inspired rigid-flexible coupling wheel design method for improving the terrain adaptability of a sewer robot.
Bioinspiration & biomimetics
May 7, 2024
The human toe, characterized by its rigid-flexible structure comprising hard bones and flexible joints, facilitates adaptive and stable movement across varied terrains. In this paper, we utilized a motion capture system to study the adaptive adjustme...
Comparing the advantages and disadvantages of physics-based and neural network-based modelling for predicting cycling power.
Journal of biomechanics
May 7, 2024
Models of physical phenomena can be developed using two distinct approaches: using expert knowledge of the underlying physical principles or using experimental data to train a neural network. Here, our aim was to better understand the advantages and ...
Graph-Driven Simultaneous and Proportional Estimation of Wrist Angle and Grasp Force via High-Density EMG.
IEEE journal of biomedical and health informatics
May 6, 2024
Myoelectric prostheses are generally unable to accurately control the position and force simultaneously, prohibiting natural and intuitive human-machine interaction. This issue is attributed to the limitations of myoelectric interfaces in effectively...
Biomechanical Posture Analysis in Healthy Adults with Machine Learning: Applicability and Reliability.
Sensors (Basel, Switzerland)
May 4, 2024
Posture analysis is important in musculoskeletal disorder prevention but relies on subjective assessment. This study investigates the applicability and reliability of a machine learning (ML) pose estimation model for the human posture assessment, whi...
Anthropomorphic Tendon-Based Hands Controlled by Agonist-Antagonist Corticospinal Neural Network.
Sensors (Basel, Switzerland)
May 3, 2024
This article presents a study on the neurobiological control of voluntary movements for anthropomorphic robotic systems. A corticospinal neural network model has been developed to control joint trajectories in multi-fingered robotic hands. The propos...
Visual feedbacks influence short-term learning of torque versus motion profile with robotic guidance among young adults.
Human movement science
May 1, 2024
Robotic assistance can improve the learning of complex motor skills. However, the assistance designed and used up to now mainly guides motor commands for trajectory learning, not dynamics learning. The present study explored how a complex motor skill...
BlazePose-Seq2Seq: Leveraging Regular RGB Cameras for Robust Gait Assessment.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 1, 2024
Evaluation of human gait through smartphone-based pose estimation algorithms provides an attractive alternative to costly lab-bound instrumented assessment and offers a paradigm shift with real time gait capture for clinical assessment. Systems based...
Temporal Variability in Stride Kinematics during the Application of TENS: A Machine Learning Analysis.
Medicine and science in sports and exercise
Apr 30, 2024
INTRODUCTION: The purpose of our report was to use a Random Forest classification approach to predict the association between transcutaneous electrical nerve stimulation (TENS) and walking kinematics at the stride level when middle-aged and older adu...
A machine-learning method isolating changes in wrist kinematics that identify age-related changes in arm movement.
Scientific reports
Apr 29, 2024
Normal aging often results in an increase in physiological tremors and slowing of the movement of the hands, which can impair daily activities and quality of life. This study, using lightweight wearable non-invasive sensors, aimed to detect and ident...
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