@inproceedings{d2708274bc6b44689a5d88739ff5a8b2,
title = "Injury Identification Using Video Magnification",
abstract = "Despite the rapid technological advancements and developments that are achieved today, correct injuries diagnose is still a regular occurring issue. There are many methods to diagnose and determine injuries, but these methods are expensive and time consuming. In this work, a portable smartphone-based video magnification (VM) technique and machine learning algorithm Haar Cascade are used to detect injuries. The main objective of this work is to develop a worldwide accessible application that detects injuries in real-time manner using video magnification of the blood's colour circulated through the injured body part. The blood flow rate is used because since injuries directly cause an increase in blood flow rate. The proposed system was successfully implemented with accuracy of 95.07\%.",
keywords = "Image Processing, Injury, Machine Learning, Video Magnification",
author = "Mohamad Alansari and Wessam Shehieb and Sara Alansari and Ayman Tawfik",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 13th Biomedical Engineering International Conference, BMEiCON 2021 ; Conference date: 19-11-2021 Through 21-11-2021",
year = "2021",
doi = "10.1109/BMEiCON53485.2021.9745207",
language = "English",
series = "BMEiCON 2021 - 13th Biomedical Engineering International Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "BMEiCON 2021 - 13th Biomedical Engineering International Conference",
address = "United States",
}