Title: IoT-Based Smart Pillow System for Early nDetection of Stroke Warning Signs through Heart Rate, Oxygen Level, and Motion Monitoring
Authors: Rogelio C. Samson, Arjay C. Marucot , Ren'z Butch S. Calma , Kimberly Dawn P. Jatulan
Volume: 10
Issue: 3
Pages: 193-198
Publication Date: 2026/03/28
Abstract:
This study presents an IoT-based smart pillow monitoring system designed to provide continuous, non-intrusive monitoring of heart rate, oxygen saturation (SpO?), and body motion as potential early indicators of stroke risk during sleep, promoting preventive healthcare and overall well-being through accessible home-based monitoring. Developed using an ESP32 microcontroller, simulated MAX30102 readings via a potentiometer, an MPU6050 motion sensor, a microphone for breathing sound detection, and a buzzer for alert notifications, the system utilizes innovative IoT and embedded technologies to support reliable and scalable health monitoring infrastructure. By emphasizing affordability and ease of deployment, the proposed system improves access to basic health monitoring for individuals with limited availability of clinical services. The system processes real-time multi-sensor data through basic filtering and threshold-based anomaly detection. Bench testing and preliminary user evaluation demonstrate that the prototype can reliably capture simulated physiological patterns, visualize them through a cloud-based dashboard, and deliver immediate alerts while maintaining user comfort. Although the system is constrained by sensor accuracy, Wi-Fi dependency, and the indirect nature of pillow-based measurements, the results confirm the feasibility of smart pillow-integrated sensing as a cost-effective solution for home-based health monitoring. This work provides a foundational framework for future enhancements, including improved sensing accuracy, long-term testing, and integration with medical-grade health platforms to further support early detection and preventive care.