AIMC Topic: Biomechanical Phenomena

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Human-in-the-Loop Myoelectric Pattern Recognition Control of an Arm-Support Robot to Improve Reaching in Stroke Survivors.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The objective of this study was to assess the feasibility and efficacy of using real-time human-in-the-loop pattern recognition-based myoelectric control to control vertical support force or vertical position to improve reach in individuals with chro...

Design and application of ISSA-BP neural network model for predicting soft tissue relaxation force.

Acta of bioengineering and biomechanics
: Accurate biomechanical modeling is crucial for enhancing the realism of virtual surgical training. This study addressed the computational cost and complexity associated with traditional viscoelastic models by incorporating neural network algorithms...

Validity of recurrent neural networks to predict pedal forces and lower limb kinetics in cycling.

Journal of biomechanics
Dynamic variables contribute to understand the mechanics of pedalling and can assist with injury prevention. Measuring pedal forces and joint moments and powers has a high cost, which can be mitigated by using trained artificial neural networks (ANN)...

HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-Body Mesh Recovery.

IEEE transactions on pattern analysis and machine intelligence
Recovering whole-body mesh by inferring the abstract pose and shape parameters from visual content can obtain 3D bodies with realistic structures. However, the inferring process is highly non-linear and suffers from image-mesh misalignment, resulting...

How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?

Sensors (Basel, Switzerland)
Upper limb training dose after stroke is usually quantified by time and repetitions. This study analyzed upper limb motor training dose in stroke participants (N = 36) using a more comprehensive approach. Participants, classified by initial motor sev...

Mechanical Structure Design and Motion Simulation Analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human-Machine Integration.

Sensors (Basel, Switzerland)
Population aging is an inevitable trend in contemporary society, and the application of technologies such as human-machine interaction, assistive healthcare, and robotics in daily service sectors continues to increase. The lower limb exoskeleton reha...

Embodied design for enhanced flipper-based locomotion in complex terrains.

Scientific reports
Robots are becoming increasingly essential for traversing complex environments such as disaster areas, extraterrestrial terrains, and marine environments. Yet, their potential is often limited by mobility and adaptability constraints. In nature, vari...

Leveraging graph neural networks and gate recurrent units for accurate and transparent prediction of baseball pitching speed.

Scientific reports
Long short-term memory (LSTM) networks are widely used in biomechanical data analysis but have the significant limitations in interpretability and decision transparency. Combining graph neural networks (GNN) with gate recurrent units (GRU) may offer ...

Using deep reinforcement learning to investigate stretch feedback during swimming of the lamprey.

Bioinspiration & biomimetics
Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion co...

Natural Language Processing and soft data for motor skill assessment: A case study in surgical training simulations.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automated surgical skill assessment using kinematic and video data (hard data) sources has been widely adopted in the literature. However, experts' opinions (soft data) in the form of free-text could be an invaluable source ...