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Skeleton

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Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

Sensors (Basel, Switzerland)
The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for early diagnosis and treatment. However, since ADHD is not a simple disease that can be diagnosed with a...

BERT for Activity Recognition Using Sequences of Skeleton Features and Data Augmentation with GAN.

Sensors (Basel, Switzerland)
Recently, the scientific community has placed great emphasis on the recognition of human activity, especially in the area of health and care for the elderly. There are already practical applications of activity recognition and unusual conditions that...

Artificial Intelligence for skeleton-based physical rehabilitation action evaluation: A systematic review.

Computers in biology and medicine
Performing prescribed physical exercises during home-based rehabilitation programs plays an important role in regaining muscle strength and improving balance for people with different physical disabilities. However, patients attending these programs ...

Multi-View Human Action Recognition Using Skeleton Based-FineKNN with Extraneous Frame Scrapping Technique.

Sensors (Basel, Switzerland)
Human action recognition (HAR) is one of the most active research topics in the field of computer vision. Even though this area is well-researched, HAR algorithms such as 3D Convolution Neural Networks (CNN), Two-stream Networks, and CNN-LSTM (Long S...

Deep Learning for Human Activity Recognition on 3D Human Skeleton: Survey and Comparative Study.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is an important research problem in computer vision. This problem is widely applied to building applications in human-machine interactions, monitoring, etc. Especially, HAR based on the human skeleton creates intuitiv...

Human Interaction Classification in Sliding Video Windows Using Skeleton Data Tracking and Feature Extraction.

Sensors (Basel, Switzerland)
A "long short-term memory" (LSTM)-based human activity classifier is presented for skeleton data estimated in video frames. A strong feature engineering step precedes the deep neural network processing. The video was analyzed in short-time chunks cre...

Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys.

Zoological research
Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction. However, action recognition currently used in non-human primate (NHP) research relies heavily on intense man...

A comparative study of the 2D- and 3D-based skeleton avatar technology for assessing physical activity and functioning among healthy older adults.

Health informatics journal
Maintaining physical activity (PA) and functioning (mobility, balance) is essential for older adults' well-being and quality of life. However, current methods (functional tests, self-reports) and available techniques (accelerometers, sensors, advanc...

On the Evaluation of Diverse Vision Systems towards Detecting Human Pose in Collaborative Robot Applications.

Sensors (Basel, Switzerland)
Tracking human operators working in the vicinity of collaborative robots can improve the design of safety architecture, ergonomics, and the execution of assembly tasks in a human-robot collaboration scenario. Three commercial spatial computation kits...

Skeleton Reconstruction Using Generative Adversarial Networks for Human Activity Recognition Under Occlusion.

Sensors (Basel, Switzerland)
Recognizing human activities from motion data is a complex task in computer vision, involving the recognition of human behaviors from sequences of 3D motion data. These activities encompass successive body part movements, interactions with objects, o...