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Implementasi Penghitung Laju Respirasi pada Sistem Polisomnografi menggunakan Mikrofon dan Arduino Nano Martin Clinton Tosima Manullang; Nova Resfita
Jurnal Teknologi Terpadu Vol. 7 No. 1: Juli, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i1.295

Abstract

Sleep apnea is a severe sleep disorder leading to severe threats such as heart attacks, strokes, diabetes, kidney failure, hypertension, etc. Not only is the diagnosis of sleep apnea a challenging measure, but it also requires a high cost of equipment, the limitations of available tools, and becomes a complicated diagnosis operated personally at home. Using the microphone embedded in the Arduino Nano, a system to measure the respiratory rate develops as a minor part of the sleep apnea diagnostic system using polysomnography. A filtering system is attached to eliminate noise and environmental consequences around the observation site. This prototype evaluates by comparing the output value with the manual calculation of the respiratory rate. Of the trials executed, the achieved system accuracy in counting the respiratory rate is above 93%, meaning that this prototype system is ideal as a method of measuring the respiratory rate.
The Implementation of Multilevel Colour Thresholding on a Prototype Coffee Machine Nova Resfita; Rahmadi Kurnia; Fitrilina Fitrilina
Journal of Science and Applicative Technology Vol 4 No 2 (2020): Journal of Science and Applicative Technology December Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/jsat.v4i2.344

Abstract

The development of computer vision has expanded widely as there is a vast number of its applications in various aspects of daily life. One of its implementations is integrating the image processing technique on a prototype coffee machine based on the speech recognition system. This study aims to detect the requested coffee colour spoken by users which are black, middle and light. The sensor used in this research is a digital PC camera and the applied method is Multilevel Colour Thresholding. Of all experiments conducted, the image processing technique can work perfectly as the camera is able to identify the requested colour of the coffee solution. Furthermore, the system might be developed by improving the multilevel colour thresholding technique as well as advancing the hardware design in order to establish more robust coffee machine based on the requested colour.