USING BODY SENSOR NETWORKS AND HUMAN ACTIVITY RECOGNITION CLASSIFIERS TO ENHANCE THE ASSESSMENT OF FORM AND EXECUTION QUALITY IN FUNCTIONAL TRAINING | Zendy

AI Assistant Blog Pricing

Open Access

USING BODY SENSOR NETWORKS AND HUMAN ACTIVITY RECOGNITION CLASSIFIERS TO ENHANCE THE ASSESSMENT OF FORM AND EXECUTION QUALITY IN FUNCTIONAL TRAINING

Author(s) -

RAFAEL DE PINHO ANDRE

Publication year - 2020

Language(s) - English

Resource type - Dissertations/theses

DOI - 10.17771/pucrio.acad.50802

Subject(s) - training (meteorology) , quality (philosophy) , computer science , artificial intelligence , activity recognition , machine learning , geography , philosophy , epistemology , meteorology

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom

About

About Careers Publisher Partners Contact Us Get Organisational Trial or Quote

Learn

FAQs Blog Terms of Use Privacy Policy

Download the Zendy App

Download on the

Discover

Explore

Copyright Knowledge E © 2026. All Rights Reserved.