AIMC Topic: Biomechanical Phenomena

Clear Filters Showing 741 to 750 of 1481 articles

Estimation of kinematics from inertial measurement units using a combined deep learning and optimization framework.

Journal of biomechanics
The difficulty of estimating joint kinematics remains a critical barrier toward widespread use of inertial measurement units in biomechanics. Traditional sensor-fusion filters are largely reliant on magnetometer readings, which may be disturbed in un...

Shoulder kinematics plus contextual target information enable control of multiple distal joints of a simulated prosthetic arm and hand.

Journal of neuroengineering and rehabilitation
BACKGROUND: Prosthetic restoration of reach and grasp function after a trans-humeral amputation requires control of multiple distal degrees of freedom in elbow, wrist and fingers. However, such a high level of amputation reduces the amount of availab...

Multidimensional Ground Reaction Forces and Moments From Wearable Sensor Accelerations via Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: Monitoring athlete internal workload exposure, including prevention of catastrophic non-contact knee injuries, relies on the existence of a custom early-warning detection system. This system must be able to estimate accurate, reliable, and...

Fundamental understanding of millipede morphology and locomotion dynamics.

Bioinspiration & biomimetics
A detailed model for the locomotory mechanics used by millipedes is provided here through systematic experimentation on the animal and validation of observations through a biomimetic robotic platform. Millipedes possess a powerful gait that is necess...

Artificial Intelligence-Assisted motion capture for medical applications: a comparative study between markerless and passive marker motion capture.

Computer methods in biomechanics and biomedical engineering
We aimed to determine whether artificial intelligence (AI)-assisted markerless motion capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is unclear whether the AI-assisted markerless method can be applied to ...

Safety Evaluation and Experimental Study of a New Bionic Muscle Cable-Driven Lower Limb Rehabilitation Robot.

Sensors (Basel, Switzerland)
Safety is a significant evaluation index of rehabilitation medical devices and a significant precondition for practical application. However, the safety evaluation of cable-driven rehabilitation robots has not been reported, so this work aims to stud...

Real-time biomechanics using the finite element method and machine learning: Review and perspective.

Medical physics
PURPOSE: The finite element method (FEM) is the preferred method to simulate phenomena in anatomical structures. However, purely FEM-based mechanical simulations require considerable time, limiting their use in clinical applications that require real...

An Accelerated Finite-Time Convergent Neural Network for Visual Servoing of a Flexible Surgical Endoscope With Physical and RCM Constraints.

IEEE transactions on neural networks and learning systems
This article designs and analyzes a recurrent neural network (RNN) for the visual servoing of a flexible surgical endoscope. The flexible surgical endoscope is based on a commercially available UR5 robot with a flexible endoscope attached as an end-e...

Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach.

Gait & posture
BACKGROUND: Gait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial acceler...