AI Medical Compendium Topic:
Biomechanical Phenomena

Clear Filters Showing 651 to 660 of 1352 articles

Motion Inference Using Sparse Inertial Sensors, Self-Supervised Learning, and a New Dataset of Unscripted Human Motion.

Sensors (Basel, Switzerland)
In recent years, wearable sensors have become common, with possible applications in biomechanical monitoring, sports and fitness training, rehabilitation, assistive devices, or human-computer interaction. Our goal was to achieve accurate kinematics e...

Estimation of Three-Dimensional Lower Limb Kinetics Data during Walking Using Machine Learning from a Single IMU Attached to the Sacrum.

Sensors (Basel, Switzerland)
Kinetics data such as ground reaction forces (GRFs) are commonly used as indicators for rehabilitation and sports performance; however, they are difficult to measure with convenient wearable devices. Therefore, researchers have attempted to estimate ...

Lower body kinematics estimation from wearable sensors for walking and running: A deep learning approach.

Gait & posture
BACKGROUND: Inertial measurement units (IMUs) are promising tools for collecting human movement data. Model-based filtering approaches (e.g. Extended Kalman Filter) have been proposed to estimate joint angles from IMUs data but little is known about ...

Learning Three Dimensional Tennis Shots Using Graph Convolutional Networks.

Sensors (Basel, Switzerland)
Human movement analysis is very often applied to sport, which has seen great achievements in assessing an athlete's progress, giving further training tips and in movement recognition. In tennis, there are two basic shots: forehand and backhand, which...

Combining wearable sensor signals, machine learning and biomechanics to estimate tibial bone force and damage during running.

Human movement science
There are tremendous opportunities to advance science, clinical care, sports performance, and societal health if we are able to develop tools for monitoring musculoskeletal loading (e.g., forces on bones or muscles) outside the lab. While wearable se...

Role of machine learning in gait analysis: a review.

Journal of medical engineering & technology
Human biomechanics and gait form an integral part of life. The gait analysis involves a large number of interdependent parameters that were difficult to interpret due to a vast amount of data and their inter-relations. To simplify evaluation, the int...

Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning.

Scientific reports
For centuries humans have been fascinated by the natural beauty of horses in motion and their different gaits. Gait classification (GC) is commonly performed through visual assessment and reliable, automated methods for real-time objective GC in hors...

Model-free motion control of continuum robots based on a zeroing neurodynamic approach.

Neural networks : the official journal of the International Neural Network Society
As a result of inherent flexibility and structural compliance, continuum robots have great potential in practical applications and are attracting more and more attentions. However, these characteristics make it difficult to acquire the accurate kinem...

Improving data acquisition speed and accuracy in sport using neural networks.

Journal of sports sciences
Video analysis is used in sport to derive kinematic variables of interest but often relies on time-consuming tracking operations. The purpose of this study was to determine speed, accuracy and reliability of 2D body landmark digitisation by a neural ...

Prediction of ground reaction force and joint moments based on optical motion capture data during gait.

Medical engineering & physics
The standard camera- and force plate-based set-up for motion analysis suffers from the disadvantage of being limited to laboratory settings. Since adaptive algorithms are able to learn the connection between known inputs and outputs and generalise th...