AI Based Patient Care Wheelchair

Abstract

The advancement of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has significantly improved healthcare monitoring and assistive mobility systems. This paper presents the design and development of an AI-based patient care wheelchair that integrates real-time health monitoring with intelligent mobility support. The system utilizes an ESP32 microcontroller as the central processing unit, connected with sensors such as the MPU6050 for motion and tilt detection and the MAX30102 sensor for monitoring blood oxygen saturation (SpO₂) and heart rate. The collected data is processed and transmitted wirelessly via Wi-Fi to a mobile application, enabling remote monitoring by caregivers. The system is capable of detecting abnormal conditions such as sudden tilt or low oxygen levels and generates instant alerts to ensure timely assistance. Additionally, the wheelchair movement is controlled using a motor driver and DC motors, allowing users to navigate independently through mobile-based commands. The proposed solution is cost-effective, reliable, and user-friendly, addressing the limitations of traditional wheelchairs by combining safety, healthcare monitoring, and mobility in a single platform. This system enhances patient independence and provides continuous supervision in healthcare environments.

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