相关论文: Predicting kinetics using musculoskeletal modeling…
In this study, we present a feedforward control system designed for active gravity compensation on an upper body exoskeleton. The system utilizes only positional data from internal motor sensors to calculate torque, employing analytical…
This paper proposes a novel orientation-aware model predictive control (MPC) for dynamic humanoid walking that can plan footstep locations online. Instead of a point-mass model, this work uses the augmented single rigid body model (aSRBM)…
Accurate understanding of muscle activation and muscle forces plays an essential role in neuro-rehabilitation and musculoskeletal disorder treatments. Computational musculoskeletal modeling has been widely used as a powerful non-invasive…
Data-driven methods have become increasingly more prominent for musculoskeletal modelling due to their conceptually intuitive simple and fast implementation. However, the performance of a pre-trained data-driven model using the data from…
Muscle force sharing is typically resolved by minimizing a specific objective function to approximate neural control strategies. An inverse optimal control approach was applied to identify the "best" objective function, among a positive…
Accurate force/torque estimation is essential for applications such as powered exoskeletons, robotics, and rehabilitation. However, force/torque estimation under dynamic conditions is a challenging due to changing joint angles, force…
In this research, we present an innovative method known as a physics-informed neural network (PINN) model to predict multi-joint kinematics using electromyography (EMG) signals recorded from the muscles surrounding these joints across…
We present a novel algorithm for online, real-time orientation estimation. Our algorithm integrates gyroscope data and corrects the resulting orientation estimate for integration drift using accelerometer and magnetometer data. This…
Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model…
This study evaluates the agreement of marker-based and markerless (OpenCap) motion capture systems in assessing joint kinematics and kinetics during cycling. Markerless systems, such as OpenCap, offer the advantage of capturing natural…
The embodied learning of human motor control requires whole-body neuro-actuated musculoskeletal dynamics, while the internal muscle-driven processes underlying movement remain inaccessible to direct measurement. Computational modeling…
This paper describes a novel method for the estimation of the trajectory curve and orientation of a rigid body moving along a railway track. Compared to other recent developments in the literature, the presented approach has the significant…
Objective: This paper presents a force control scheme for brief isotonic holds in an isometrically contracted muscle tissue, with minimal overshoot and settling time to measure its shortening velocity, a key parameter of muscle function.…
This study presents an innovative computer vision framework designed to analyze human movements in industrial settings, aiming to enhance biomechanical analysis by integrating seamlessly with existing software. Through a combination of…
Full-body motion estimation of a human through wearable sensing technologies is challenging in the absence of position sensors. This paper contributes to the development of a model-based whole-body kinematics estimation algorithm using…
The use of exoskeleton robots is increasing due to the rising number of musculoskeletal injuries. However, their effectiveness depends heavily on the design of control systems. Designing robust controllers is challenging because of…
Balance, gait and postural control are some of the key factors in determining the overall stability of an individual. Several highend and costly solutions exist to perform movement analysis in clinical settings. OpenSim is a tool which uses…
Ionic Polymer Metal Composites (IPMCs) are one of the most preferred choices among biocompatible materials for industrial and biomedical applications. Despite their advantages, some of their drawbacks include non-linear and hysteretic…
Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has excelled in biophysical parameter estimation tasks from…
Intravoxel incoherent motion (IVIM) is a diffusion-weighted magnetic resonance imaging (MRI) method that may be applied to the placenta to help diagnose abnormal pregnancies. IVIM requires prolonged scan times, followed by a model-based…