An Experimental Survey with NodeMCU12e+Shield with Tft Nextion and MAX30102 Sensor

Bento, Antonio Carlos

doi:10.1109/iemcon51383.2020.9284870

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…From the results of the calibration test in Table 4 and Table 5, all the RMSE values obtained were less than 3.5%. Based on research [25], if the RMSE value of a pulse oximeter is less than 3.5%, the sensor has fairly good accuracy and can be used for testing.…”

Section: Resultsmentioning

confidence: 99%

Detection of Oxygen Levels (SpO2) and Heart Rate Using a Pulse Oximeter for Classification of Hypoxemia Based on Fuzzy Logic

Dini

Rakhmatsyah²,

Wardana³

2022

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

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This study made the digital system to perform screening (early prediction) of Hypoxemia using MAX30102 sensor with the fuzzy value from SpO2 level and heart rate. This research also uses the Internet of Things (IoT) system to gather data from devices to the cloud. Hypoxemia is a lack of oxygen in the blood flowing in the body. Hypoxemia conditions in the body due to lack of oxygen levels in the blood will cause an increased heart rate. Hypoxemia conditions that are not immediately recognized cause damage to cells, tissues, and organs. Hypoxemia is an essential condition because information about oxygen levels in the blood is closely related to health conditions. In this project, researchers built a Hypoxemia early detection system. From the research results, it is found that the accuracy rate of the system to detect hypoxemia is 80%, with 60% sensitivity and 100% specificity. Based on the experiment, this research is able to help screening detection (early prediction) of Hypoxemia.

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Section: Resultsmentioning

confidence: 99%

Detection of Oxygen Levels (SpO2) and Heart Rate Using a Pulse Oximeter for Classification of Hypoxemia Based on Fuzzy Logic

Dini

Rakhmatsyah²,

Wardana³

2022

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

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“…MAX30102 functioning was fully validated and comprised of an optical module of 5.6 mm × 3.3 mm × 1.55 mm 14-pin with low-power HR monitor (<1 mW) and an ultra-low shutdown current of 0.7 µA, as well as robust motion artifact resilience and −40 • C to +85 • C operating temperature range. It could be supplied with a single 1.8 V source, or a separate 3.3 V [20,21]. Moreover, ESP32 was also used.…”

Section: Methodsmentioning

confidence: 99%

MAX30102 Photometric Biosensor Coupled to ESP32-Webserver Capabilities for Continuous Point of Care Oxygen Saturation and Heartrate Monitoring

Contardi

Morikawa

Brunelli

et al. 2021

The 2nd International Electronic Conference on Biosensors

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“…Arduino Mega operates at a clock speed of 16 MHz, which allows fast processing of instructions [24], [25]. In this research, Arduino Mega is used to read data from DHT22, MLX90614, and MAX30102 sensors, each of which measures parameters such as temperature, heart rate, and blood oxygen level [26]- [28]. In the system configuration process, the DHT22 sensor is connected to the Arduino Mega via a digital pin, enabling data communication between the two.…”

Section: Hardware Designmentioning

confidence: 99%

Developing a smart system for infant incubators using the internet of things and artificial intelligence

Aryanto,

Maneetham,

Triandini

2024

IJECE

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This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R<sup>2</sup> value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R<sup>2</sup> value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.

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An Experimental Survey with NodeMCU12e+Shield with Tft Nextion and MAX30102 Sensor

Cited by 9 publications

References 9 publications

Detection of Oxygen Levels (SpO2) and Heart Rate Using a Pulse Oximeter for Classification of Hypoxemia Based on Fuzzy Logic

Detection of Oxygen Levels (SpO2) and Heart Rate Using a Pulse Oximeter for Classification of Hypoxemia Based on Fuzzy Logic

MAX30102 Photometric Biosensor Coupled to ESP32-Webserver Capabilities for Continuous Point of Care Oxygen Saturation and Heartrate Monitoring

Developing a smart system for infant incubators using the internet of things and artificial intelligence

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