Design and prototyping of an AI-powered wearable device for continuous vital signs monitoring with intelligent alerting

This work addresses the growing demand for affordable, wearable, and continuous health monitoring, particularly for patients, seniors, and athletes. It presents a wearable system for monitoring five vital signs: heart rate (HR), body temperature (T), blood oxygen saturation (SpO₂), blood pressure (BP), and respiratory rate (RR). All these parameters are measured using a single MAX30102 module without the need for a cuff or any additional sensors. Using advanced MATLAB signal processing, we have developed a random forest regression method, which, after simplification into a quadratic equation, estimates BP and RR with good accuracy. All recorded data are time-stamped and geotagged on a memory card, enabling patient history to support improved diagnostics. This compact, cost-effective device tracks vital signs and features intelligent alerts-audible alarms notify users of abnormalities. In critical situations, real-time vital signs and GPS coordinates are transmitted to the next of kin for emergency response. This combination of practical design and AI-powered analysis provides an effective solution for personal and clinical applications. Evaluation results demonstrate high accuracy: SpO₂ at 98.74 ± 0.99, T at 98.56 ± 0.48, HR at 95.47 ± 4.31, RR at 95.01 ± 0.96, and clinically acceptable BP estimates (systolic 94.20 ± 8.24, diastolic 92.68 ± 7.37).