AIMC Topic: Movement

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Football Movement Profile-Based Creatine-Kinase Prediction Performs Similarly to Global Positioning System-Derived Machine Learning Models in National-Team Soccer Players.

International journal of sports physiology and performance
PURPOSE: The relationship between external load and creatine-kinase (CK) response at the team/position or individual level using Global Positioning Systems (GPS) has been studied. This study aimed to compare GPS-derived and Football Movement Profile ...

A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot.

Biochemical and biophysical research communications
To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidi...

Deep Learning for hand tracking in Parkinson's Disease video-based assessment: Current and future perspectives.

Artificial intelligence in medicine
BACKGROUND: Parkinson's Disease (PD) demands early diagnosis and frequent assessment of symptoms. In particular, analysing hand movements is pivotal to understand disease progression. Advancements in hand tracking using Deep Learning (DL) allow for t...

Human Joint Angle Estimation Using Deep Learning-Based Three-Dimensional Human Pose Estimation for Application in a Real Environment.

Sensors (Basel, Switzerland)
Human pose estimation (HPE) is a technique used in computer vision and artificial intelligence to detect and track human body parts and poses using images or videos. Widely used in augmented reality, animation, fitness applications, and surveillance,...

An optimized EEGNet decoder for decoding motor image of four class fingers flexion.

Brain research
As a cutting-edge technology of connecting biological brain and external devices, brain-computer interface (BCI) exhibits promising applications on extensive fields such as medical and military. As for the disable individuals with four limbs losing t...

Investigating the impact of initial parameters on autonomous robot swarm movement strategies for enhanced exploration efficiency: a comprehensive study.

Bioinspiration & biomimetics
Swarm robots are frequently preferred for the exploration of harsh environments and search and rescue operations. This study explores the factors that influence the movement strategies of autonomous robot swarms and their impact on swarm distribution...

A virtual rodent predicts the structure of neural activity across behaviours.

Nature
Animals have exquisite control of their bodies, allowing them to perform a diverse range of behaviours. How such control is implemented by the brain, however, remains unclear. Advancing our understanding requires models that can relate principles of ...

Deep learning of Parkinson's movement from video, without human-defined measures.

Journal of the neurological sciences
BACKGROUND: The core clinical sign of Parkinson's disease (PD) is bradykinesia, for which a standard test is finger tapping: the clinician observes a person repetitively tap finger and thumb together. That requires an expert eye, a scarce resource, a...

An Experiment Using Functional Near-Infrared Spectroscopy and Robot-Assisted Multi-Joint Pointing Movements of the Lower Limb.

Journal of visualized experiments : JoVE
Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise in helping stroke patients regain lost motor functions. One potential avenue for increasing the ...

Basketball technique action recognition using 3D convolutional neural networks.

Scientific reports
This research investigates the recognition of basketball techniques actions through the implementation of three-dimensional (3D) Convolutional Neural Networks (CNNs), aiming to enhance the accurate and automated identification of various actions in b...