Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics

Compared RGB Methods Towards Efficient Money Detector for Blind People

2024-03-10T04:11:12+00:00

Limitations of profound visual impairment distinguishing each nominal number of banknotes are often used by people with bad intentions to take advantage of that basis, like money fraud. Due to this reason, the blind people need to be helped to recognize their surroundings by developing assistive technology that is advanced for them. This study aims to build an efficient design of a money detector by comparing three RGB methods: range breakdown, If-Then Rules, and decision tree to recognize the nominal of money. The sample used in this experiment is rupiah banknotes for the 2016 and 2022 issuances. The device is built with a TCS3200 colour sensor and designed in a real-time platform. It has been found that the highest average percentage accuracy was achieved by the breakdown range method with 100% (2016 sample) and 90% (2022 sample). This device also successfully produced a notification sound from a speaker that mentions the detected nominal value. This research could be used as a reference to improve assistive technology for blind people.

Monitoring Baby Incubator Central through Internet of Things (IoT) based on Raspberry Pi Zero W with Personal Computer View

2024-03-10T04:10:39+00:00

kids born before 37 weeks of pregnancy or weighing less than 2500 grams are considered premature, whereas kids born between 38 and 40 weeks of pregnancy and between 2500 to 4000 grams are considered full-term. Given that their organ systems are still developing within the womb, premature infants find it difficult to adjust to life outside the womb. As a result, special consideration must be made. They include modifying the environment's temperature, humidity, and oxygen needs to reflect those of the mother's womb. These conditions might be replaced with a baby incubator. This tool's creation is intended to make it easier for midwives and other healthcare professionals to keep an eye on many baby incubators. The Internet of Things (IoT) system is used by this instrument to transfer data. Using three ESP32 modules that have been put together to create modules that can collect data and have that data analyzed by a server (central monitoring) Raspberry Pi Zero W. Data will be sent via Internet of Things (IoT) technology, and the website will display the data. Two tests were conducted at 32 degrees Celsius, one at 34 degrees Celsius, and one at 36 degrees Celsius for a total of five tests. This technique was developed using a form of pre-experimental, after-only study. In this configuration, researchers may only see the module reading results; incubator analyzer data are not shown. Error value 3 in monitoring at 32 degrees Celsius has a maximum error of -0.04 percent. The largest error value occurs when the temperature is set to 34 degrees Celsius, when the monitoring error value is -0.016%. Monitoring inaccuracy is at its highest, 0.01%, when the temperature is 36 degrees Celsius. The monitoring 3 error value is most at 32 degrees Celsius (-0.025 percent), followed by 34 degrees Celsius (0.031 percent), and finally 36 degrees Celsius (0.049 percent), as shown by data on noise measurements. The findings demonstrate that each measurement performed by the module still contains mistakes. Medical staff should find it easier to concurrently monitor many infant incubators thanks to this discovery.

Fuzzy Logic Temperature Control on Blood Warmer Equipped with Patient Temperature and Blood Temperature

2024-03-10T06:00:19+00:00

Body temperature in humans varies greatly depending on the location where the reading is taken. Normal core body temperature in humans is maintained by the hypothalamus and usually ranges from 36.5°C to 37.5°C. One of the causes of the failure of Too high or too low of a temperature during the blood transfusion procedure may cause blood to freeze or get damaged, both of which can be fatal to humans, therefore the purpose of this tool is to lower blood temperature admission to the patient can be achieved so that there is no temperature drop or temperature drop and so that the blood is not too hot because it can cause damage to red blood cells. This study uses the DS18B20 Sensor to control the heater with PID and Fuzzy controls, the MLX90614 Sensor to adjust the temperature according to the patient's body temperature and the Optocoupler Sensor as an indicator when fluids run out. Previous studies have not used the MLX90614 sensor to detect patient body temperature, have not used TFT Nextion and have not used Fuzzy controls. This Fuzzy control is used as a heater control which then the results are displayed on the Nextion TFT. The results of this study obtained the highest error value of 0.09 with an average error value of 0.04 and obtained the highest overshoot value of 0.8. From the results of the above study it can be concluded that by using the Fuzzy control the response time is slower with a larger overshoot. In the creation of this tool, the benefits that can be derived for the community are facilitating the monitoring of patient temperature and blood temperature during blood transfusions using the Blood Warmer device. The device is also equipped with sensors to detect patient and blood temperatures, and it comes with a Nextion TFT display. Therefore, this device is crucial in assisting the community in performing Blood Transfusions.

Spo2 Analysis on Development of IoT-Based Lung Function and Spo2 Measuring Device

2024-03-10T04:59:53+00:00

Pulmonary dysfunction is a widespread issue, particularly in developing nations. It encompasses restrictive, obstructive, and mixed pulmonary function disorders that lead to a decrease in vital lung capacity, an increase in functional residual capacity, and a decline in blood oxygen concentration and saturation. This study aims to combine oximetry and spirometry into a single device, using the Internet of Things (IoT) technology to display results via a smartphone app. The focus is on analyzing oxygen saturation, with normal levels ranging from 96% to 100% in adults, alongside a heart rate of 60-100 beats per minute. The MAX30102 sensor measures oxygen saturation, and the Arduino Pro Mini and D1 Mini ESP32 microcontrollers process data. The Android-based app, developed using Kodular platform, integrates a MySQL database and connects to the device module via Wi-Fi. Ten respondents underwent five measurements, revealing an average error of ±0.88% for oxygen saturation (SpO₂) and ±2.82% for heart rate measurements. The average data loss rate during transmission was ±0.66% for SpO₂ and ±0.89% for heart rate. These findings highlight existing errors in the module. The research aims to facilitate remote health monitoring for healthcare professionals, improving accessibility and healthcare provision.

Design and Development of an IoT-based Pulmonary Function and Oxygen Saturation Measurement Device

2024-03-16T15:13:09+00:00

Health information technology plays a crucial role in managing the healthcare of patients and their families during illness. One of the frequently encountered diseases is Asthma, a chronic inflammatory disorder of the respiratory tract that is reversible and fluctuating, capable of causing exacerbations with mild to severe symptoms and even death. The objective of this research is to develop a device to facilitate the monitoring and input of data regarding pulmonary volume measurements (spirometry) and biosignals (SpO2). The sensors used for measuring pulmonary volume are the flow turbine sensor, while the SpO2 sensor used is the MAX30102. The data obtained from the sensor measurements will be processed on the ESP32. A health monitoring application is created using Kodular software, which incorporates a MySQL database for data storage. Furthermore, the examination results can be accessed through an Android application on a tablet or smartphone. The results obtained from this research indicate an error value of 8.78% for FVC, 14% for FEV1, and a FEV1/FVC ratio of 4.6%, with zero data loss. It is expected that the spirometer with Internet of Things (IoT) capabilities will be implemented, as monitoring can be easily conducted anywhere. The portable design will facilitate future examinations.

Revolutionizing Waste Management: A Cutting-edge pyTorch Model for Waste Classification and Prediction, Coupled with a User-friendly Recycling Recommendation Application Built with Tkinter

2024-03-10T05:20:06+00:00

A major environmental concern is waste management, and encouraging recycling programs depends heavily on the accurate categorization and forecasting of waste kinds. We present an enhanced pytorch model in this work for waste prediction and classification. To promote sustainable waste disposal practices, we also present a Recycling Recommendation Application with an intuitive Tkinter interface. The goal of combining cutting-edge machine learning methods with user-centered design is to make waste management systems more effective. The model gained accuracy of 99% on training and approximately 96% on validation, and was successfully added in a tkinter app for making prediction on type of waste image, plus recommending of solution to such waste management is done by the application we develop.

A Fuzzy Logic Approach to Enhance GPS Accuracy for Blood Cooler Box Tracking

2024-03-10T05:56:46+00:00

An innovative technological development, the position tracking system uses latitude and longitude coordinates to determine the GPS's location. The covid-19 pandemic has caused the demand for cool box delivery for convalescent blood plasma to increase significantly. The obstacle in the field is the hospital's position and patient rooms far from the reach convalescent donors, so they require a cool box for delivery. The problem is tracking the cool box accurately and precisely so that it can be monitored by the hospital properly. For this reason, it is necessary to increase the accuracy of the GPS position in the cool box by using fuzzy logic algorithms The Ublox NEO-6M is one GPS module that can be utilized for navigation. This module uses UART connection using the NMEA 0183 protocol and has an accuracy level of around 2.5 meters to 10 meters. In this research, validation of the accuracy of the GPS coordinate position was carried out on a Blood Cool Box device which was designed using the fuzzy logic method. The Sugeno method fuzzy logic algorithm is used to validate the accuracy of GPS coordinate positions based on latitude and longitude obtained from the GPS sensor module. The test results show a Mean Absolute Percent Error (MAPE) value of 21.66% which can be concluded that the Sugeno fuzzy logic method algorithm has forecasting model capabilities that are suitable for use as a validation method for testing GPS position coordinates.

Communication Prototype for Post-Stroke Patients Using Electrooculography (EOG)

2024-03-10T06:08:21+00:00

The background of this prototype is meant for post-stroke patients who have difficulties owing to trouble completing daily activities, particularly speaking with others. They have trouble communicating, which reduces their quality of life after a stroke. The goal of developing novel communication aids for post-stroke patients is to make it easier for post-stroke patients to communicate with caretakers. Electrooculography (EOG) signals generated by the movement of the eye muscles during eye glances collected by the MaM Sense sensor are employed in post-stroke communication aids. The microcontroller processes the method's command signal, which is subsequently displayed on a 20 x 4 Character LCD. For the four communications utilized, the MaM Sense sensor reading was successful 80.5% of the time. Thus, communication tools for post-stroke patients can help them communicate while also assisting caretakers in understanding the patient's wants. Improvements will be made in the design and wireless technologies for EOG signal recovery in the future.