Penerapan Logika Fuzzy Mamdani dan Sensor MAX30100 untuk Penilaian Kondisi Pasien Kardiovaskular: Penelitian - Nazila, Millati; Budisusila, Eka Nuryanto (Lembaga Penelitian dan Pengabdian Masyarakat, 2025)
Monitoring cardiovascular patients at home is often constrained by the interpretation of raw sensor data. This service aimed to implement a portable decision support system to convert raw heart rate (BPM) and oxygen saturation (SpO2) data into meaningful health condition information. The method used was designing a prototype based on NodeMCU ESP8266 and the MAX30100 sensor for data acquisition , and applying Mamdani Fuzzy Logic for analysis. A Fuzzy Inference System (FIS) in MATLAB used 9 rule-bases to classify 2 inputs (BPM and SpO2) into 3 outputs ('Healthy', 'Caution', 'Emergency'). The case study object was a patient with a history of hypertensive heart disease and aortic aneurysm. The results showed the prototype had high accuracy, reaching 95.98% for heart rate and 95.31% for oxygen saturation. The fuzzy logic system successfully classified 35 test datasets, with 34 detected as