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http://dx.doi.org/10.6109/jkiice.2021.25.12.1949

Design and performance evaluation of deep learning-based unmanned medical systems for rehabilitation medical assistance  

Choi, Donggyu (Department of Computer Engineering, Dong-Eui University)
Jang, Jongwook (Department of Computer Engineering, Dong-Eui University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.12, 2021 , pp. 1949-1955 More about this Journal
Abstract
With the recent COVID-19 situation, countries are seriously feeling the need for medical personnel and their technologies. PDepending on the aging society, the number of medical staff is actually decreasing, and in order to solve this problem, research is needed to replace the part that does not require high expertise among actual medical practices performed by doctors. This paper describes and proposes actual research methods related to unmanned medical systems that use various deep learning image processing-based technologies to check the recovery status applicable to rehabilitation areas where medical staff should face patients directly. The proposed method replaces passive calculations such as a protractor or a method of drawing a line in a photograph, which is the method used for actual motion comparison. Since it is performed in real time, it helps to diagnose quickly, and it is easy for medical staff to provide necessary information because data on the degree of match of motion performance can be checked.
Keywords
Deep learning; Image processing; Object detection; Rehabilitation medical; Unmanned medical system;
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