AIMC Topic: Movement

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Optimal position fuzzy control for coordinated movement of the ring and little fingers in an impaired human hand.

Biological cybernetics
The dexterity of the human hand is largely due to its multiple degrees of freedom. However, coordinating the movements of the ring and little fingers independently can be challenging because of the biomechanical and neurological interdependencies bet...

AI-Driven Tai Chi mastery using deep learning framework for movement assessment and personalized training.

Scientific reports
This paper presents a novel system for optimizing Tai Chi movement training using computer vision and deep learning technologies. We developed a comprehensive framework incorporating multi-view pose estimation, temporal feature extraction, and real-t...

Instantaneous center of rotation, the first step to build up the digital laboratory of complex motions.

PloS one
Calculating instantaneous centers of rotation to describe combined rotational and translational motions has a long history in many fields of applied science and basic rigid body kinematics. However, only some theoretical studies have explored the fun...

Robust skeletal motion tracking using temporal and spatial synchronization of two video streams.

PloS one
Accurate and reliable skeletal motion tracking is essential for rehabilitation monitoring, enabling objective assessment of patient progress and facilitating telerehabilitation applications. Traditional marker-based motion capture systems, while high...

Neural Signals-Based Respiratory Motion Tracking: A Surface Electromyography Study.

International journal of radiation oncology, biology, physics
PURPOSE: Neural signals-based respiratory motion tracking offers a potential solution to the system latency issue of medical linear accelerators in respiratory motion tracking radiation therapy. However, decoding respiratory-related neural signals fr...

Learning behavior aware features across spaces for improved 3D human motion prediction.

Scientific reports
3D skeleton-based human motion prediction is an essential and challenging task for human-machine interactions, aiming to forecast future poses given a history of previous motions. However, most existing works model human motion dependencies exclusive...

Personalized ML-based wearable robot control improves impaired arm function.

Nature communications
Portable wearable robots offer promise for assisting people with upper limb disabilities. However, movement variability between individuals and trade-offs between supportiveness and transparency complicate robot control during real-world tasks. We ad...

The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns.

Scientific reports
The diverse nature and timing of a clubfoot relapse pose challenges for early detection. A relapsed clubfoot typically involves a combination of deformities affecting a child's movement pattern across multiple joint levels, formed by a complex kinema...

Enhancing surface electromyographic signal recognition accuracy for trans-radial amputees using broad learning systems.

Biomedical physics & engineering express
Gesture recognition based on surface electromyography (sEMG) plays a crucial role in human-computer interaction. By analyzing sEMG signals generated from residual forearm muscle activity in trans-radial amputees, it is possible to predict their hand ...

A hybrid model for detecting motion artifacts in ballistocardiogram signals.

Biomedical engineering online
BACKGROUND: The field of contactless health monitoring has witnessed significant advancements with the advent of piezoelectric sensing technology, which enables the monitoring of vital signs such as heart rate and respiration without requiring direct...