Development of ECG sensor using arduino uno and e-health sensor platform: mood detection from heartbeat

Rumpa, Lantana Dioren; Suluh, Sallolo; Ramopoly, Irene Hendrika; Jefriyanto, Wilson

doi:10.1088/1742-6596/1528/1/012043

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…Table 3 lists the specifications of each of the Arduino platforms that were evaluated. In the literature, while Arduino Uno [38,42], and Arduino Mega [43][44][45] are the most popular microcontroller options for usage with the AD8232, we have discounted Mega owing to its large footprint. We have implemented the prototype on an Arduino MKR 1010 (Arduino, Italy) owing to its 12-bit resolution, large flash memory, in-built Bluetooth feature, multiple PWM-enabled pins (see Table 3) and the fact that it is about ten years newer than other models, and to the best of our knowledge, has not been evaluated for ECG signal processing.…”

Section: Choice Of Microcontrollermentioning

confidence: 99%

Internet of Things-Based ECG and Vitals Healthcare Monitoring System

et al. 2022

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Health monitoring and its associated technologies have gained enormous importance over the past few years. The electrocardiogram (ECG) has long been a popular tool for assessing and diagnosing cardiovascular diseases (CVDs). Since the literature on ECG monitoring devices is growing at an exponential rate, it is becoming difficult for researchers and healthcare professionals to select, compare, and assess the systems that meet their demands while also meeting the monitoring standards. This emphasizes the necessity for a reliable reference to guide the design, categorization, and analysis of ECG monitoring systems, which will benefit both academics and practitioners. We present a complete ECG monitoring system in this work, describing the design stages and implementation of an end-to-end solution for capturing and displaying the patient’s heart signals, heart rate, blood oxygen levels, and body temperature. The data will be presented on an OLED display, a developed Android application as well as in MATLAB via serial communication. The Internet of Things (IoT) approaches have a clear advantage in tackling the problem of heart disease patient care as they can transform the service mode into a widespread one and alert the healthcare services based on the patient’s physical condition. Keeping this in mind, there is also the addition of a web server for monitoring the patient’s status via WiFi. The prototype, which is compliant with the electrical safety regulations and medical equipment design, was further benchmarked against a commercially available off-the-shelf device, and showed an excellent accuracy of 99.56%.

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Section: Choice Of Microcontrollermentioning

confidence: 99%

Internet of Things-Based ECG and Vitals Healthcare Monitoring System

et al. 2022

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“…Also provided on this board are RA (Right Arm), LA (Left Arm), and RL (Right Leg) pins to attach and use your own custom sensors. Additionally, there is an LED indicator light that will pulsate to the rhythm of a heartbeat [11].…”

Section: Electrocardiograph Ecg Sensormentioning

confidence: 99%

Design and Implementation of a Smart, Interactive and Portable System for Monitoring of Human Vital Signs

Shahadi

Kadhim²,

Almeyali³

et al. 2021

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

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Smart systems are characterized by their efficiency, high accuracy, and cost reduction. One of the important fields in which the smart system is used is health care, especially monitoring of human vital signs. In general, the conventional patient monitor is expensive, cannot be used for remote monitoring, and non-interactive. In many situations, it requires remote and portable monitoring for patients, such as in case of the area is outside the medical services, infected diseases (e.g., 20), and difficulties of a patient transferred. This paper proposes a smart, interactive, and portable monitor for vital human signs based on the Internet of Things (IoT). The proposed monitor is cheap and easy to use either directly by doctors and nurses or remotely by any person. The proposed system is designed using ESP32microcontroller and vital-sign sensors. It measures three important vital signs, including heart rate, body temperature, and Electrocardiography (ECG), as well as the environment temperature of the patient. The measured signs can be monitored from anywhere in the world through a smartphone application in real-time. Furthermore, the doctor can send instructions and descriptions to the patients in real-time using the same phone application that is designed in this work.

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“…For instance, one study utilized an Arduino UNO microcontroller with a nasal cannula pressure transducer for detecting obstructive sleep apnea (OSA) events [15]. Another proposed an E-Health Sensor Platform v2.0, comprising numerous sensors linked with an Arduino Uno to assess various aspects of human biology, including heart rate, breathing, and skin conductance [5]. However, these methods require further validation and comparative studies to establish their efficacy informed healthcare decisions.…”

Section: Introductionmentioning

confidence: 99%

Embedded IoT Data Collection for Snore Analysis

2024

IJATCSE

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Internet of Things (IoT)-based devices are in demand for capturing different data types to produce essential information for the receiver. Human sleep behavior is one area open for research, particularly on human snoring. The ESP32 microcontroller was used to modify the processes of capturing human snoring during sleep. This embedded IoT-based device monitors and captures the snoring activity of the human being while sleeping. A prototype of the modified device with its new algorithm was developed, and different test experiments were conducted to test its system performance. Experiment results showcased the accuracy of capturing snoring frequencies beyond established norms and measuring decibel levels within specific parameters. Technical challenges were encountered, such as static interferences and data storage errors, but all were systematically addressed, highlighting the system's robustness. Pilot experiments on EXP1 and EXP2 provided insights into the system's adaptability to different environmental conditions. It is recommended to incorporate upgraded machine learning algorithms into a more powerful microcontroller to improve noise differentiation and computational capabilities and to collaborate with sleep experts to enable diagnostic capabilities. The research emphasizes the system's potential for real-world application in advancing healthcare solutions while highlighting the need for continuous evolution

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Development of ECG sensor using arduino uno and e-health sensor platform: mood detection from heartbeat

Cited by 7 publications

References 2 publications

Internet of Things-Based ECG and Vitals Healthcare Monitoring System

Internet of Things-Based ECG and Vitals Healthcare Monitoring System

Design and Implementation of a Smart, Interactive and Portable System for Monitoring of Human Vital Signs

Embedded IoT Data Collection for Snore Analysis

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