RANCANG BANGUN ALAT PENDETEKSI GLUKOSA DENGAN METODE NON-INVASIVE BERBASIS MACHINE LEARNING MENGGUNAKAN SENSOR GSR (GALVANIC SKIN RESISTANCE) - Afini, M. Dwi Nur; Nurussa’adah, n/a; Purnomowati, Endah Budi (Jurnal Mahasiswa TEUB, 2024)
Stroke is a sudden onset of neurological disorders, either focal or global, associated with cerebral circulation disorders. Strokes typically last more than 24 hours and can result in death without a known cause. It is a disease in which blood flow to the brain is obstructed, preventing the supply of oxygen and nutrients and the removal of waste products. This leads to rapid death of brain cells. The success of stroke management is highly dependent on time. Providing prompt first aid yields better clinical outcomes. However, monitoring body conditions is often neglected, and non-invasive tools for measuring blood sugar levels are lacking, which can be traumatic for users. From an economic standpoint, checking blood sugar levels is considered costly. To address these issues, technology is needed to non-invasively and regularly monitor the condition of stroke patients. The technology canprimarily monitor one of the risk factors for stroke, namely blood sugar, using a Galvanic Skin Resistance (GSR) sensor. The sensor classifies the patient's condition and provides education on reducing these risk factors. The tool's function has been tested by comparing the results of laboratory measurements, which showed an accuracy rate of 96.49% for blood sugar levels. During the testing of the monitoring application supported by the ANFIS system, the classification results of the user's condition were obtained with 100% accuracy. The testing was conducted on five patients who had high risk factors for stroke. Keywords: Stroke, Photoplethysmograph, Monitoring Application, ANFIS, Therapy.