Scopus Indexed Publications

Paper Details

Estimating Energy Expenditure of Push-Up Exercise in Real Time Using Machine Learning
Md. Shoreef Uddin, Sadman Saumik Islam,

The Covid-19 pandemic has nearly brought the globe to a standstill. However, we were able to adjust to the circumstance with the aid of computer technology by working remotely from home. Health and fitness have grown to be top priorities during these tumultuous times when people are confined to their homes. By completing certain easy physical activities that don’t require any special equipment and can be done at home, a person can maintain good health and fitness. Furthermore, the detection and recognition of human body motions or gestures is not a new concept when using artificial intelligence. Analysis of human body movement is now quicker and easier because of the development of real-time detection and identification technologies like YOLO. In this study, we have employed YOLO V4 as an AI helper to detect and identify push-ups from a real-time video stream recorded from a webcam or a smartphone camera that may be used to aid with push-ups. In order to keep the system affordable, we are recommending an approach that can identify pushups and estimate energy usage in real-time without the use of additional sensors or other wearable gadgets."

"Health and Fitness Push-up Exercise Energy Expenditure Home-Based Exercise Program"
Journal or Conference Name
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Publication Year