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The current (mA) control is necessary to controlling the number of electrons and x-ray intensity at x-ray machine. Radiographers are likewise impacted by the presence of high radiation levels. This study aimed to improve performance the x-ray machine with wireless mA control system prototype. One of the important benefits of the proposed study is the simplicity to controlling intensity of x-ray based on wireless mA control system. This research method uses rheostat as current selection (mA). The current settings that can be selected are 20 mA, 30 mA, 40 mA, 50 mA and 60 mA, which can be done manually and via the mobile phone (cellphone) connected to this device via wireless using Wemos D1Mini. Tool testing is carried out by comparing the results of measuring the output voltage of the filament transformer using AVOmeter with the results of voltage calculation through formula analysis. In addition, tests are carried out for the distance of the tool control connection in the presence of obstacles and no obstacles. Based on the test results obtained, it is known that the smallest correction value is 0,01 VAC for the mA option of 30 mA. The x-ray device can be controlled wirelessly using Android up to a distance of 20 meters with a 14 cm thick wall obstructed condition. [ABSTRACT FROM AUTHOR]

A high voltage (kV) on the x-ray device is necessary to create x-ray radiation. High voltage (kV) is created by the High Tension Transformator (HTT), which increases the Alternating Current (AC) voltage from the Volt (V) scale to Kilo Volt (kV). However, many regional public hospitals in Indonesia continue to employ X-ray equipment with analog kV selection systems. As a result, radiographers will be continuously exposed to radiation since they must directly operate the instrument. This project aims to develop a wireless kV controller prototype for x-ray equipment to decrease radiographers' radiation exposure. This study methodology comprises four major phases: hardware design, software design, voltage suitability testing on x-ray instruments, and wireless remote-control testing. This study uses Android smartphones to set the kV parameter. The WEMOS D1 MINI and the Arduino MEGA 2560 microcontroller are used for serial connection. The selectable kV options are 40kV, 50kV, 60kV, and 70kV, whose outputs are emulated with 300V, 350V, 400V, and 450V. The largest adjustment is +9.263V at the 60kV level, while the smallest is +2.316V at the 40kV setting. The adjustment value is still within the 5 percent tolerance value limit. With a barrier wall thickness of 14 centimetres, the farthest distance measured was 20 meters. [ABSTRACT FROM AUTHOR]

The heart is a primary organ inside the human body. Therefore, it is necessary to take care of their health. One way to find out his health is by monitoring the heart itself. In monitoring the heart, it is very necessary to store monitoring results to facilitate the medical team or doctors in conducting patient examinations. Therefore, a research was conducted to design or create a heart signal data logger system as a modification of an electrocardiograph commonly known as a holter monitor. From the results of measuring the amplitude of the R wave height on the holter monitor and the original ECG with phantom input, the average relative error is 3.67% and the length of the R to R distance is -23.8%. Then from the results of measuring the amplitude of the R wave height on the Holter monitor and the original ECG with the same input from the same patient in four different positions. The lying position has a relative error value of -73,3%, sitting position -53.8%, standing position -45.2%, and walking position -56.6%. Whilst, for the length of the distance from R to R, the lying position has a relative error value of 10.3%, the sitting position is 33.3%, the standing position is -10%, and the walking position is 29.4%. [ABSTRACT FROM AUTHOR]

Cardiac abnormalities can be identified by diagnosing heart sounds obtained from the mechanical activity of the heart which is censored by a pre-amp condenser mic stethoscope. The signal from the sensor will be processed in the filter circuit and ADC, in the data processor to be displayed on the LCD the authors use Raspberry Pi as a microprocessor. The process of monitoring is done by displaying a signal on the LCD. Based on the results of measurements on 10 people that their heart conditions are normal and displayed a systolic graph (S1) is heard when the mitral and tricuspid valves of the heart close and diastolic (S2) is heard when the aortic and pulmonary valves close. The experimental results can be stored on the SD Card and can be used for the doctors in analyzing and diagnosing heart conditions. In the results of the function test and patient trials on the Phonocardiography (PCG) device with a Raspberry Pi processor, the device can work well as confirmed by the sound of S1 and S2. [ABSTRACT FROM AUTHOR]