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ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units.
Jeon, Sanghoon; Ko, Byuk Sung; Son, Sang Hyuk.
  • Jeon S; Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul 04763, Republic of Korea.
  • Ko BS; Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul 04763, Republic of Korea.
  • Son SH; Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
Sensors (Basel) ; 23(2)2023 Jan 05.
Article in English | MEDLINE | ID: covidwho-2166824
ABSTRACT
With advances in the Internet of Things, patients in intensive care units are constantly monitored to expedite emergencies. Due to the COVID-19 pandemic, non-face-to-face monitoring has been required for the safety of patients and medical staff. A control center monitors the vital signs of patients in ICUs. However, some medical devices, such as ventilators and infusion pumps, operate in a standalone fashion without communication capabilities, requiring medical staff to check them manually. One promising solution is to use a robotic system with a camera. We propose a real-time optical digit recognition embedded system called ROMI. ROMI is a mobile robot that monitors patients by recognizing digits displayed on LCD screens of medical devices in real time. ROMI consists of three main functions for recognizing digits digit localization, digit classification, and digit annotation. We developed ROMI by using Matlab Simulink, and the maximum digit recognition performance was 0.989 mAP on alexnet. The developed system was deployed on NVIDIA GPU embedded platforms Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. We also created a benchmark by evaluating the runtime performance by considering ten pre-trained CNN models and three NVIDIA GPU platforms. We expect that ROMI will support medical staff with non-face-to-face monitoring in ICUs, enabling more effective and prompt patient care.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Experimental Studies Limits: Humans Language: English Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Experimental Studies Limits: Humans Language: English Year: 2023 Document Type: Article