AI Medical Compendium Journal:
Journal of biomechanics

Showing 71 to 80 of 83 articles

A learning-based markerless approach for full-body kinematics estimation in-natura from a single image.

Journal of biomechanics
We present a supervised machine learning approach for markerless estimation of human full-body kinematics for a cyclist from an unconstrained colour image. This approach is motivated by the limitations of existing marker-based approaches restricted b...

Improving the ground reaction force prediction accuracy using one-axis plantar pressure: Expansion of input variable for neural network.

Journal of biomechanics
In this study, we describe a method to predict 6-axis ground reaction forces based solely on plantar pressure (PP) data obtained from insole type measurement devices free of space limitations. Because only vertical force is calculable from PP data, a...

Artificial neural networks to predict 3D spinal posture in reaching and lifting activities; Applications in biomechanical models.

Journal of biomechanics
Spinal posture is a crucial input in biomechanical models and an essential factor in ergonomics investigations to evaluate risk of low back injury. In vivo measurement of spinal posture through the common motion capture techniques is limited to equip...

Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

Journal of biomechanics
Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limi...

Sex-based differences in knee ligament biomechanics during robotically simulated athletic tasks.

Journal of biomechanics
ACL injury rates are greater in female athletes than their male counterparts. As female athletes are at increased risk, it is important to understand the underlying mechanics that contribute to this sex bias. The purpose of this investigation was to ...

Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.

Journal of biomechanics
One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to si...

Predicting manual arm strength: A direct comparison between artificial neural network and multiple regression approaches.

Journal of biomechanics
In ergonomics, strength prediction has typically been accomplished using linked-segment biomechanical models, and independent estimates of strength about each axis of the wrist, elbow and shoulder joints. It has recently been shown that multiple regr...

A scalable, high resolution strain sensing matrix suitable for tactile transduction.

Journal of biomechanics
The integration of tactile information, such as contact area, displacement magnitude, velocity, and acceleration, is paramount to the optimization of robotics in human-centric environments. Cost effective embeddable sensors with scalable receptive fi...

Can shoulder joint reaction forces be estimated by neural networks?

Journal of biomechanics
To facilitate the development of future shoulder endoprostheses, a long term load profile of the shoulder joint is desired. A musculoskeletal model using 3D kinematics and external forces as input can estimate the mechanical load on the glenohumeral ...

Validation of a six degree-of-freedom robotic system for hip in vitro biomechanical testing.

Journal of biomechanics
Currently, there exists a need for a more thorough understanding of native hip joint kinematics to improve the understanding of pathological conditions, injury mechanisms, and surgical interventions. A biomechanical testing system able to accomplish ...