Designing IoT-Based Independent Pulse Oximetry Kit as an Early Detection Tool for Covid-19 Symptoms

Hidayat, Alfin; Subono,; Wardhany, Vivien Arief; Nugroho, Ajie Setyo; Hakim, Sofyan; Jhoswanda, Mirtha; Syamsiana, Ika Noer; Agustina, Nur Anis

doi:10.1109/ic2ie50715.2020.9274663

Cited by 31 publications

(16 citation statements)

References 7 publications

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“…The system can transmit data over the network without human-computer interaction. Pulse blood sampling kits proposed by paper [ 46 ] are also a means of remote screening. With the help of IoT technology, remote physical intensive care of COVID-19 patients can be performed via intelligent mobile devices.…”

Section: Remote Intensive Care For Patients With Covid-19mentioning

confidence: 99%

AIoT Used for COVID-19 Pandemic Prevention and Control

Chen

Wang

et al. 2021

Contrast Media & Molecular Imaging

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The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a vital role in preventing the spread of the pandemic of COVID-19. AI and 5G technologies are advancing by leaps and bounds, further strengthening the intelligence and connectivity of IoT applications, and conventional IoT has been gradually upgraded to be more powerful AI + IoT (AIoT). For example, in terms of remote screening and diagnosis of COVID-19 patients, AI technology based on machine learning and deep learning has recently upgraded medical equipment significantly and has reshaped the workflow with minimal contact with patients, so medical specialists can make clinical decisions more efficiently, providing the best protection not only to patients but also to specialists themselves. This paper reviews the latest progress made in combating COVID-19 with both IoT and AI and also provides comprehensive details on how to combat the pandemic of COVID-19 as well as the technologies that may be applied in the future.

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Section: Remote Intensive Care For Patients With Covid-19mentioning

confidence: 99%

AIoT Used for COVID-19 Pandemic Prevention and Control

Chen

Wang

et al. 2021

Contrast Media & Molecular Imaging

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“…Like, In [4], where a MAX30100 sensor that attached to ESP32 microprocessor in order to collect patient's heart rate and Spo2, and the results are sent to a server using the MQTT protocol and Wi-Fi technology. In [3], a similar system utilizing using NodeMCU and smartphones for remote temperature control.…”

Section: Sim I L a R Wo R K Smentioning

confidence: 99%

“…The gathered data can then be sent to a server or a cloud using a wireless connection. These connections include but not limited to Bluetooth, Wi-Fi, 4G, 3G, and GPRS [3], [6], [13]- [17]. The collected data could be sent to cloud storage to perform permanent storage or monitoring in real-time [13].…”

mentioning

confidence: 99%

“…A mobile applications can be used to observe the patient's information easily [14], [15]. This system is expected to monitor patients' Pulse Rate and Temperature, while doctors monitor the patient's condition remotely without being physically present near the patient's bed [3], [4], [14]. The doctors w ill produce more accurate results for diagnosing a patient's medical problem, which resulted from observing abnormal Pulse Rate and Temperature readings [4], [5].…”

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confidence: 99%

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Cloud-based COVID-19 Patient Monitoring using Arduino

Hanoon

Aal-Nouman

2021

2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT)

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IoT is considered as one of the fastest growing technology in the medical and industrial fields, and one of its use is the transmission of the Medical information of the patients to the general practice (GP) or hospitals. And because of the last situation of the COVID-19, and the increasing number of the infected people, the researchers started to focus on how to transmit and monitor the patients information remotely in order to decrease the chance of infection. This paper introduces an affordable IoT-based application aiming to decreases the chance of COVID-19 infection transmission. The proposed device can help the patients by checking their health status, while doctors remotely monitor this information. This paper presents a measuring and recording device for heart rate, oxygen saturation levels, and body temperature. An Arduino device with sensors will be used to measure these records and send them to the cloud server. The results show that the information has been sent successfully to the cloud.

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“…Hence, continuous and real-time monitoring of the respiratory system is essential for timely detection, tracking of the current situation, progression, and treatment response of infected patients. Any abnormality in the respiratory system can help predict the disease before the onset of the visible symptoms [32]. The other two basic and vital signs to detect asymptomatic suspects are the level of oxygen saturation (SpO 2 ) and the HR.…”

Section: Rule-based Fuzzy Logic Classifier For Covid-19 Detection (Flcd)mentioning

confidence: 99%

Symptom Analysis Using Fuzzy Logic for Detection and Monitoring of COVID-19 Patients

et al. 2021

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Recent developments regarding the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) opened new horizons of healthcare opportunities. Moreover, these technological advancements give strength to face upcoming healthcare challenges. One of such challenges is the advent of COVID-19, which has adverse effects beyond comprehension. Therefore, utilizing the basic functionalities of IoT, this work presents a real-time rule-based Fuzzy Logic classifier for COVID-19 Detection (FLCD). The proposed model deploys the IoT framework to collect real-time symptoms data from users to detect symptomatic and asymptomatic Covid-19 patients. Moreover, the proposed framework is also capable of monitoring the treatment response of infected people. FLCD constitutes three components: symptom data collection using wearable sensors, data fusion through Rule-Based Fuzzy Logic classifier, and cloud infrastructure to store data with a possible verdict (normal, mild, serious, or critical). After extracting the relevant features, experiments with a synthetic COVID-19 symptom dataset are conducted to ensure effective and accurate detection of COVID-19 cases. As a result, FLCD successfully acquired 95% accuracy, 94.73% precision, 93.35% recall, and showed a minimum error rate of 2.52%.

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Designing IoT-Based Independent Pulse Oximetry Kit as an Early Detection Tool for Covid-19 Symptoms

Cited by 31 publications

References 7 publications

AIoT Used for COVID-19 Pandemic Prevention and Control

AIoT Used for COVID-19 Pandemic Prevention and Control

Cloud-based COVID-19 Patient Monitoring using Arduino

Symptom Analysis Using Fuzzy Logic for Detection and Monitoring of COVID-19 Patients

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