The importance of respiration rates and oxygen saturation (SpO2) monitoring and the high need for oxygen therapy opens the opportunity for the development of non-invasive respiration rate and oxygen saturation monitoring and controlling system. There are two modes of controlling in this system, automatic and manual mode. In automatic mode, the oxygen flow rate is based on the measurement of the respiration rate using the MLX90614 temperature sensor and tidal volume determination based on the patient’s body weight. Oxygen flow control uses a DC motor to open and close the oxygen regulator valve. Oxygen flow will stop when the respiration rate and oxygen saturation level are normal. Oxygen saturation is measured using the MAX30100 sensor. The fabricated regulator control system is capable of flowing oxygen by 5-8 liters per minute using an oxygen mask. The respiration rate measurement was compared with the palpation test, and the deviation was 0.99%. Oxygen saturation reading that used MAX30100 as an oximeter sensor was compared with pulse oximeter fingertip reading, and the deviation was 1.62%. The average flow deviation between the fabricated regulator control system and the calibrated regulator is 2.93%. The result of measuring the response time of the motor for an increase of one liter per minute (LPM) is 1.54 seconds.

Blood pressure monitor (BPM) using oscillometric method with MPX5050GP pressure sensor has been successfully fabricated and calibrated. Oscillometric method is measurement method to observe cuff pressure oscillations. In this study, the oscillometric waveform measured by fabricated BPM used Arduino Uno which processes pulse rate, systolic and diastolic pressures. Measurement results of pulse rate, systolic and diastolic pressures will be displayed and recorded in application designed using Visual C# 2010 Express. Fabricated BPM capable of measuring pulse rate and blood pressure in the range of 40-260 mmHg with ratio of systolic and diastolic pressures were achieved 0.48 and 0.78, respectively. The system has an average error of systolic pressure, diastolic pressure, and pulse rate were-4.38 mmHg (2.72%), 0.10 mmHg (5,55%), and 4.48 bpm (6.07%).

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The planar scintigraphic image usually has poor resolution and contains noise. This noise can be removed using the coiflet wavelet method so that the image quality gets better. This coiflet wavelet method is a noise reduction method based on frequency analysis. The planar scintigraphy image is the reconstructed image of the gamma radiation count data (phantom with the Cs-137 source in it). The original image is 15×15 pixel. Before the de-noising process, the image went through an interpolation process, which is to increase the pixel size of the image. The original image enlarged to 70×70, 480×480, and 1200×1200 pixel. After de-noising with coiflet wavelet, the image quality is measured based on MSE and PSNR parameters. The resulting images are quite good, with MSE values are close to zero and PSNR values of more than 60 dB. The smaller the MSE and the bigger the PSNR, is getting the better the image quality. In this study, the results show that the 1200×1200 pixel image has the best quality. It means that the image enlargement process has a good effect on the de-noising process, especially if the original image has a low resolution.