Evidence map›Paper›PMID 36679435›Full record

ArticleSensors (Basel, Switzerland)2023

ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units.

Sanghoon Jeon, Byuk Sung Ko, Sang Hyuk Son

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Sanghoon JeonDepartment of Emergency Medicine, College of Medicine, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0000-0001-5636-7555
Byuk Sung KoDepartment of Emergency Medicine, College of Medicine, Hanyang University, Seoul 04763, Republic of Korea.
Sang Hyuk SonDepartment of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea.
Hanyang University · KRDaegu Gyeongbuk Institute of Science and Technology · KR

Funding

Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education 2021R1I1A1A01040943Bio & Medical Technology Development Program of the National Research Foundation(NRF) & funded by the Korean government(MSIT) NRF-2019M3E5D1A01066060Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No.2020-0-01373, Artificial Intelligence Graduate School Program(Hanyang University)) and the research fund of Hanyang University HY-202100000670023National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT) 2018R1A5A1060031
6 · The paper itself

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.

Indexed as

COVID-19HumansIntensive Care UnitsMonitoring, PhysiologicPandemicsVital Signsembedded systemsintensive care unitsmedical devicesoptical digit recognitionreal-time monitoring

Identifiers

PMID36679435
PMCPMC9867275
OpenAlexW4313640353

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.