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All Journal Jurnal Sehat Mandiri International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE)
Andy Sambiono
Poltekkes Kemenkes Jakarta II
Computer Science & IT Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Medicine & Pharmacology Public Health

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RANCANG BANGUN SISTEM PEMUTUS ARUS SEBAGAI PENGAMAN TEMPERATUR BERLEBIH PADA INKUBATOR BAYI Indah Nursyamsi Handayani; Wike Kristianti; Mamurotun Mamurotun; Andy Sambiono
Jurnal Sehat Mandiri Vol 16 No 1 (2021): Jurnal Sehat Mandiri, Volume 16, No.1 Juni 2021
Publisher : Poltekkes Kemenkes Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (177.058 KB) | DOI: 10.33761/jsm.v16i1.331

Abstract

Several countries in the world, including Indonesia, have reported baby-care accidents in the baby incubator due to the failure of the temperature control system to maintain a stable temperature. Therefore, this study reports the design of an circuit breaker system as an over-temperature safety in a baby incubator. Experimentally, the prototype consists of hardware design, software design, and testing system design. The hardware design has four main part, sensing layer using PT1000 as a temperature sensor, data processing layer using an ESP32 microcontroller, a circuit breaker system using a solid-state relay as an electronic switching, and LCD as a display. System testing has been done by evaluating the temperature readings on a prototype against the HTC-02 digital thermometer instrument and carried out in the electromedical engineering laboratory. The results show the accuracy of the temperature parameter is 99% and the circuit breaker system is able to cut the current from the power supply to the appliance when the temperature is more than 39°C which is indicated by an incandescent lamp "off" where this is equivalent to a heater at the baby incubator is in the "off" condition. From the results of this test, it can be concluded that the circuit breaker system as a safety over temperature in the baby incubator has functioned according to the design.Recommended the development of this prototype needs to be followed up by testing on low-tech baby incubators available at basic health care facilities so as to improve technology readiness to be effective in the community.
Implementation of Thermal Camera for Human Stress Detection: A Review Atika Hendryani; Vita Nurdinawati; Andy Sambiono
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 1 No. 2 (2023)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v1i2.28

Abstract

Stress has become a major problem that people face today. The high level of competition and environmental demands make people more susceptible to stress. Stress can interfere with a person's ability to work effectively. If left unchecked for a long time, stress can cause various dangerous diseases such as hypertension, heart problems, and others that can lead to death. Research has been conducted for a long time to detect stress. Various technologies have been used to detect and anticipate stress that occurs in humans. One promising technology for detecting stress is the use of thermal cameras. Thermal cameras have several advantages: being non-contact and non-invasive, quick, easy to use, and cost-effective. In general, the architecture of the stress detection system using a thermal camera consists of several stages, including image acquisition, pre-processing, ROI tracking and selection, feature extraction, and statistical analysis or classification. This paper aims to review the use of thermal cameras in detecting stress in humans. This paper also seeks to answer the research question of what analysis can be done to improve stress detection accuracy using thermal camera images. Research shows that ROI selection must be carefully considered to obtain good accuracy. Combining thermal images with other data can improve accuracy in stress detection. Machine learning in classification provides many benefits in recognizing patterns but is highly influenced by the number of datasets used.
Co-Authors Atika Hendryani Handayani, Indah Nursyamsi Mamurotun Mamurotun Vita Nurdinawati Wike Kristianti