Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Classification of Bones

Classification of Bones

The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...

Carbon Skeletons

Carbon Skeletons

Life on Earth is carbon-based, as all macromolecules that make up living organisms contain carbon atoms. All organic compounds have a carbon backbone. Each carbon atom is tetravalent and can bond with four other atoms, making it an extraordinarily flexible component of biological molecules. Because carbon’s valence electrons are stable, it rarely becomes an ion. As the carbon chain increases in length, structural modifications such as ring structures, double bonds, and branching side...

Classification of Skeletal Muscle Fibers

Classification of Skeletal Muscle Fibers

Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

TrustInAging: Digital Tools for Healthy Aging.

Studies in health technology and informatics·2026

Same author

Rapid e-Delphi Design of a Survey on Student Lifestyles, Psychological, and Contextual Factors Integrating the World Mental Health International College Student Assessment in the Italian Higher Education Setting.

International journal of methods in psychiatric research·2026

Same author

Interplay between balance, gait kinematic and physical activity level in facioscapulohumeral muscular dystrophy.

Scientific reports·2025

Same author

Deep Learning Models Optimization for Gait Phase Identification from EMG Data During Exoskeleton-Assisted Walking.

Biomimetics (Basel, Switzerland)·2025

Same author

Four-Week Exoskeleton Gait Training on Balance and Mobility in Minimally Impaired Individuals with Multiple Sclerosis: A Pilot Study.

Bioengineering (Basel, Switzerland)·2025

Same author

Power Output, Lactatemia, and Maximum Oxygen Consumption During a Specific Off-Water Incremental Test in International-Level Podium-Winner Kayak and Rowing Athletes.

Journal of functional morphology and kinesiology·2025

Search research articles

Related Experiment Video

Updated: Dec 6, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

Skeleton data pre-processing for human pose recognition using Neural Network.

Bruna M V Guerra, Stefano Ramat, Roberto Gandolfi

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|October 6, 2020

Summary

This summary is machine-generated.

This study enhances automatic activity recognition for frail individuals using skeleton data. Pre-processing Kinect data significantly improved pose recognition accuracy for daily living activities.

More Related Videos

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

Related Experiment Videos

Last Updated: Dec 6, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

Area of Science:

Computer Science
Biomedical Engineering
Human-Computer Interaction

Background:

Automatic monitoring of daily living activities supports autonomy for frail individuals.
Skeleton tracking offers a privacy-preserving method for activity recognition and fall detection.
Kinect-based skeleton data can be prone to errors under non-ideal tracking conditions.

Purpose of the Study:

To investigate the benefits of pre-processing Kinect-recorded skeleton data.
To improve the accuracy of pose recognition for daily living activities.
To enhance the reliability of automatic monitoring systems for elderly or frail individuals.

Main Methods:

Pre-processing of Kinect-recorded skeleton data to mitigate tracking errors.
Utilizing a two hidden layers Multi-Layer Perceptron (MLP) classifier.
Training and testing the classifier on four distinct poses: standing, sitting, lying, and dangerous sitting.

Main Results:

Pre-processing significantly reduced errors in skeleton tracking data.
The MLP classifier's accuracy in recognizing four key poses improved from approximately 82% to over 92%.
Enhanced accuracy demonstrates the effectiveness of the proposed pre-processing technique.

Conclusions:

Pre-processing Kinect skeleton data is crucial for improving the accuracy of activity recognition.
The enhanced pose recognition system can reliably identify daily living activities and potentially dangerous situations.
This approach contributes to safer and more independent living for frail individuals through improved monitoring.