In the medical world, patient safety is a top priority. The large number of workloads and the frequency of using the devices in the long run will affect the accuracy and accuracy of the tool. If the flow rate and volume of the syringe pump or infusion pump given to the patient are not controlled (overdose or the fluid flow rate is too high) it can cause hypertension, heart failure or pulmonary edema. Therefore, it is necessary to have a calibration, which is an application activity to determine the correctness of the designation of the measuring instrument or measuring material. The purpose of this research is to make a two channel infusion device analyzer using a photodiode sensor. The contribution of this research is that the system can display three calibration results in one measurement at the same setting and can calibrate 2 tools simultaneously. The design of the module is in the form of an infrared photodiode sensor for reading the flowrate value. This study uses an infrared photodiode sensor for channels 1 and 2 installed in the chamber. This study uses a flow rate formula that is applied to the water level system to obtain 3 calibration results. Infrared photodiode sensor will detect the presence of water flowing in the chamber from an infusion or syringe pump. Then the sensor output will be processed by STM32 and 3 calibration results will be displayed on the 20x4 LCD. This tool has an average error value on channel 1 of 3.50% and on channel 2 of 3.39%. It can be concluded that the whole system can work well, the placement and distance between the infrared photodiodes also affects the sensor readings
Human limb amputation can be caused due to congenital disabilities, accidents, and certain diseases. Amputation caused by occupational accidents is a frequent occurrence in developing countries. Meanwhile, amputation caused by certain diseases such as diabetes Miletus is also the leading cause. The need for prosthetic hand is increasing along with the increase in those two factors. Several researchers have developed prosthetic hands with advantages and disadvantages. Research on prosthetic hands, which are useful, low power, and low cost, is still a major issue. Therefore, the purpose of this paper is to provide a review of the various designs of prosthetic hands, specifically on the sensor, control, and actuator systems. This paper collected several references from proceedings and journals related to the design of the prosthetic hand. The results show that the EMG signal is widely used by some researchers in controlling prosthetic hands compared to other sensors, following the force-sensitive resistor (FSR) sensor. To control prosthetic hands, some researchers used a threshold system with a value of 20% of the maximum voluntary contraction (MVC), and several other researchers used a pattern recognition model based on the EMG signal feature. Moreover, In the mechanical part, the open-source prosthetic hand model is more widely used than the fabricate prosthetic hand. This is due to the cost required in the prosthetic hand design is cheaper than a fabricated one. The results of this review are expected to provide a recommendation to researchers in the development of low cost, low power, and practical prosthetic hands.
Electrocardiograph (ECG) menjadi salah satu ilmu diagnostik yang sering dipelajari dalam mendiagnosis dan untuk terapi penyakit jantung. Mengingat pentingnya alat ECG recorder, maka diperlukan pengecekan fungsi alat ECG recorder yaitu dengan cara melakukan prosedur kalibrasi alat menggunakan Phantom ECG. Tujuan dari penelitian ini adalah membuat ECG Simulator untuk alat ECG 12 channel yang meliputi lead I, lead II, lead III, aVR, aVF, aVL, V1, V2, V3, V4, V5, dan V6 dan melengkapinya dengan selektor pemilihan sensitivitas serta menggunakan. Metode pembentukan sinyal jantung menggunakan DAC tipe MCP 4921 dengan mikrokontroler Atmega2560 dan untuk tampilan pengaturanya menggunakan LCD Karakter 2x16. Berdasarkan hasil pengukuran didapat nilai tingkat kesalahan sebesar 0.187% sensitivitas 0.5mV dan 0.327% sensitivitas 1.0mV pada setting BPM 30, didapat nilai tingkat kesalahan sebesar 1.173% sensitivitas 0.5mV dan 1.060% sensitivitas 1.0mV pada setting BPM 60, didapat nilai tingkat kesalahan sebesar 0.797% sensitivitas 0.5mV dan 0.739% sensitivita 1.0mV pada setting BPM 120, didapat nilai tingkat kesalahan sebesar 0.269% sensitivitas 0.5mV dan 0.381% sensitivitas 1.0mV pada setting BPM 180 dan 0.010% sensitivitas 0.5mV dan 0.616% sensitivitas 1.0mV pada setting BPM 240. Modul ECG Simulator dilengkapi dengan fitur charge baterai dan biaya pembuatan yang lebih murah dibandingkan dengan alat pabrikan.
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