Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul 04763, Republic of Korea.
Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
Sensors (Basel). 2023 Jan 5;23(2):638. doi: 10.3390/s23020638.
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.
随着物联网的发展，重症监护病房的患者不断被监测以加快应对紧急情况。由于 COVID-19 大流行，为了患者和医务人员的安全，需要进行非面对面监测。一个控制中心监测重症监护病房患者的生命体征。然而，一些医疗设备，如呼吸机和输液泵，独立运行，没有通信能力，需要医务人员手动检查。一个有前途的解决方案是使用带有摄像头的机器人系统。我们提出了一个名为 ROMI 的实时光学数字识别嵌入式系统。ROMI 是一个移动机器人，通过实时识别医疗设备液晶显示屏上显示的数字来监测患者。ROMI 由识别数字的三个主要功能组成：数字定位、数字分类和数字注释。我们使用 Matlab Simulink 开发了 ROMI，在 alexnet 上的最大数字识别性能为 0.989 mAP。该开发系统部署在 NVIDIA GPU 嵌入式平台上：Jetson Nano、Jetson Xavier NX 和 Jetson AGX Xavier。我们还通过考虑十个预先训练的 CNN 模型和三个 NVIDIA GPU 平台来评估运行时性能，创建了一个基准。我们希望 ROMI 将支持重症监护病房的医务人员进行非面对面监测，从而实现更有效和及时的患者护理。
