AIMC Topic: Biomechanical Phenomena

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Comparing the Lower-Limb Muscle Activation Patterns of Simulated Walking Using an End-Effector-Type Robot with Real Level and Stair Walking in Children with Spastic Bilateral Cerebral Palsy.

Sensors (Basel, Switzerland)
Cerebral palsy is a neurologic disorder caused by lesions on an immature brain, often resulting in spasticity and gait abnormality. This study aimed to compare the muscle activation patterns of real level and stair walking with those of simulated wal...

A Morphologically Individualized Deep Learning Brain Injury Model.

Journal of neurotrauma
The brain injury modeling community has recommended improving model subject specificity and simulation efficiency. Here, we extend an instantaneous (< 1 sec) convolutional neural network (CNN) brain model based on the anisotropic Worcester Head Injur...

Synergistic Integration of Skeletal Kinematic Features for Vision-Based Fall Detection.

Sensors (Basel, Switzerland)
According to the World Health Organisation, falling is a major health problem with potentially fatal implications. Each year, thousands of people die as a result of falls, with seniors making up 80% of these fatalities. The automatic detection of fal...

Artificial Intelligence Distinguishes Pathological Gait: The Analysis of Markerless Motion Capture Gait Data Acquired by an iOS Application (TDPT-GT).

Sensors (Basel, Switzerland)
Distinguishing pathological gait is challenging in neurology because of the difficulty of capturing total body movement and its analysis. We aimed to obtain a convenient recording with an iPhone and establish an algorithm based on deep learning. From...

Closed-Chain Inverse Dynamics for the Biomechanical Analysis of Manual Material Handling Tasks through a Deep Learning Assisted Wearable Sensor Network.

Sensors (Basel, Switzerland)
Despite the automatization of many industrial and logistics processes, human workers are still often involved in the manual handling of loads. These activities lead to many work-related disorders that reduce the quality of life and the productivity o...

The concepts of muscle activity generation driven by upper limb kinematics.

Biomedical engineering online
BACKGROUND: The underlying motivation of this work is to demonstrate that artificial muscle activity of known and unknown motion can be generated based on motion parameters, such as angular position, acceleration, and velocity of each joint (or the e...

Kinematic modelling and experimental testing of a particle-jamming soft robot based on a DEM-FEM coupling method.

Bioinspiration & biomimetics
Particle-jamming soft robots are characterised by high flexibility in motion and high stiffness when executing a task. Regarding particle jamming of soft robots, the discrete element method (DEM)-finite element method (FEM) coupling was used for mode...

Effect of Gait Speed on Trajectory Prediction Using Deep Learning Models for Exoskeleton Applications.

Sensors (Basel, Switzerland)
Gait speed is an important biomechanical determinant of gait patterns, with joint kinematics being influenced by it. This study aims to explore the effectiveness of fully connected neural networks (FCNNs), with a potential application for exoskeleton...

Source Aware Deep Learning Framework for Hand Kinematic Reconstruction Using EEG Signal.

IEEE transactions on cybernetics
The ability to reconstruct the kinematic parameters of hand movement using noninvasive electroencephalography (EEG) is essential for strength and endurance augmentation using exoskeleton/exosuit. For system development, the conventional classificatio...

Visual Gait Analysis Based on UE4.

Sensors (Basel, Switzerland)
With the development of artificial intelligence technology, virtual reality technology has been widely used in the medical and entertainment fields, as well as other fields. This study is supported by the 3D modeling platform in UE4 platform technolo...