Portable ECG System Design Using the AD8232 Microchip and Open-Source Platform

Bravo-Zanoguera, Miguel E.; Cuevas-González, Daniel; García-Vázquez, Juan Pablo; Avitia, Roberto L.; Reyna, M. A.

doi:10.3390/ecsa-6-06584

Cited by 16 publications

(13 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In an ECG signal, the R-wave represents the patient's heartbeat [29]. We determine the main "R" peaks for each patient's ECG signal, as well as the typical period of the signal amplitude (figure 7).…”

Section: Detection Of the Number Of Beatsmentioning

confidence: 99%

IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal

Sakli,

Baccouch,

Bellali

et al. 2023

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

In this work, our contribution will intervene to reduce the impact of noises on the ECG signals. Various ECG denoising approaches were tested to see how efficient they were in removing dominant noises that add to pure ECG signals. Due to different causes such as interference, muscular noise, body movement related to breathing, and so on, the original signal acquired by the electrodes produces noises. In this article, the electrode signals are monitored using an Internet of Things system that combines an Arduino board and an AD8232 module to generate a one-dimensional signal. These ECG signals are displayed on a computer using the Matlab interface. Following that, an efficient deep learning model was developed to facilitate cardiologists in their diagnosis of ECG signals. These experimental results obtained demonstrate the effectiveness of our proposed model compared to other existing methods in the literature. Finally, the filtered and classified ECG signals are given to the doctor for correct treatment of the patient's condition.

show abstract

Section: Detection Of the Number Of Beatsmentioning

confidence: 99%

IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal

Sakli,

Baccouch,

Bellali

et al. 2023

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

show abstract

“…In the system studied in [20], the ECG signal is collected by an AD8232 sensor. Then, the signal is digitized using the 10-bit Analog-to-Digital converter (ADC) of the ATmega328 microcontroller.…”

Section: Related Workmentioning

confidence: 99%

A Wireless ECG Monitoring and Analysis System Using the IoT Cloud

Bushnag¹

2022

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

A portable electrocardiogram (ECG) monitoring system is essential for elderly and remote patients who are not able to visit the hospital regularly. The system connects a patient to his/her doctor through an Internet of Things (IoT) cloud server that provides all the information needed to diagnose heart diseases. Patients use an ECG monitoring device to collect and upload information regarding their current medical situation via the Message Queue Telemetry Transport (MQTT) protocol to the server. The IoT cloud server performs further analysis that can be useful for both the doctor and the patient. Moreover, the proposed system has an alert mechanism that sends notifications when a certain threshold is reached. The monitoring system accepts two types of input data: real-time data that are collected by an ECG device and benchmark data from the PhysioNet ECG-ID database. The system framework has four components: input, embedded device, IoT cloud server, and interface. Herein, two experiments are conducted using both types of input data. The results show that the proposed system provides reliable and trusted results that might reduce the number of required hospital visits. A comparison between the proposed system and several techniques previously reported in the literature is conducted. Finally, an implementation of the proposed system is presented to illustrate its operation.

show abstract

“…The AD8232 module in combination with an Arduino has been used in prior studies for heartbeat detection (e.g. Bhosale & Bhosale, 2016;Bravo-Zanoguera, Cuevas-González, García-Vázquez, Avitia, & Reyna, 2019;Kanani & Padole, 2018;Simanjuntak, Khodra, & Manullang, 2020). However, in order to make it easier for researchers to reconstruct the ArdMob-ECG for use in further studies, the current paper will also provide the code and a clear schematic of the hardware.…”

Section: An Arduino-based Ecg Device Using the Ad8232 Modulementioning

confidence: 99%

An Arduino based heartbeat detection device (ArdMob-ECG) for real-time ECG analysis

Möller¹,

Voss²,

Kaltwasser³

2022

Preprint

View full text Add to dashboard Cite

This technical paper provides a tutorial to build a low-cost (10-100 USD) and easy to assemble ECG device (ArdMob-ECG) that can be easily used for a variety of different scientific studies. The advantage of this device is that it automatically stores the data and has a built-in detection algorithm for heartbeats. Compared to a clinical ECG, this device entails a serial interface that can send triggers via USB directly to a computer and software (e.g. Unity, Matlab) with minimal delay due to its architecture. Its software and hardware is open-source and publicly available. The performance of the device regarding sensitivity and specificity is comparable to a professional clinical ECG and is assessed in this paper. Due to the open-source software, a variety of different research questions and individual alterations can be adapted using this ECG. The code as well as the circuit is publicly available and accessible for everyone to promote a better health system in remote areas, Open Science, and to boost scientific progress and the development of new paradigms that ultimately foster innovation.

show abstract

Portable ECG System Design Using the AD8232 Microchip and Open-Source Platform

Cited by 16 publications

References 2 publications

IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal

IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal

A Wireless ECG Monitoring and Analysis System Using the IoT Cloud

An Arduino based heartbeat detection device (ArdMob-ECG) for real-time ECG analysis

Contact Info

Product

Resources

About