RANCANG BANGUN SMART WATCH PENGUKUR DENYUT NADI, TEKANAN DARAH DAN OXYMETER NONINVASIVE DENGAN SELECTIVE WAVELENGTH SENSOR BERBASIS IOT - Prabowo, Muhamad Romadhani; Nurussa’adah, n/a; Hasanah, Rini Nur (Jurnal Mahasiswa TEUB, 2024)
Stroke is a focal or global neurological disorder that occurs acutely and is related to cerebral circulation disturbances. It occurs when blood cannot reach the brain to supply oxygen and nutrients and to remove waste products, which can lead to brain cell death. Stroke recurrence can be prevented by controlling risk factors such as hypertension, heart disease, and diabetes mellitus. More than 50% of stroke cases are related to hypertension, while 1 in 4 cases are related to high levels of bad cholesterol (Low-Density Lipoprotein/LDL). The aim of this research is to design a wireless sensor system that can measure heart rate, oxygen level, and blood pressure non-invasively, which can be integrated with a microcontroller for transmission to monitoring devices.Photoplethysmography (PPG), as a non-invasive tool for monitoring various cardiovascular parameters, has become popular due to its easy integration with wearable devices and its uniform properties. This research proposes the development of an advanced PPG sensor design using three LED light variants as a light source with fixed wavelengths. The proposed sensor will be integrated with a smartwatch capable of operating in the Internet of Things (IoT) network, creating a more holistic and digitally connected monitoring system. From the testing results of the PPG sensor on the noninvasive smartwatch for measuring heart rate, bloodpressure, and oximeter with selective wavelength sensor based on IoT, the accuracy level of blood pressure readings was found to be 99.8%, heart rate 99.48%, and oxygen levels 99.96%. Testing was performed by comparing the reading data with reference data from commercial sphygmomanometers and oximeters. The smartwatch uses Bluetooth Low Energy communication protocol tocommunicate with Android device applications. The received data is processed and stored in Firebase Cloud Storage. Users can monitor reading history and predict the risk of ischemic stroke. Keywords: Photoplethysmography, Stroke, Internet of Things, MAX30105, ESP32