AI DRIVEN TALKING HEALTH MANAGEMENT SYSTEM
T. Jayasree, M. Vaibhavadarani, K. Oviya
Department of Biomedical Engineering, College of Engineering Guindy, Anna University, Chennai, India.
Abstract. The proposed work introduces a novel approach to healthcare monitoring, leveraging voice-enabled technology to provide real-time health status updates in local languages. While tele-medicine has been implemented in certain rural areas, this system goes a step further by integrating voice-based communication, making it accessible to all groups of people, regardless of literacy or language proficiency. The system uses IoT-based sensors to monitor vital signs such as heart rate, blood oxygen saturation (SpO2), body temperature, and respiration rate. These data, combined with user-reported symptoms, are processed using machine learning algorithms to predict diseases and provide actionable insights. The system delivers real-time feedback, health education, and emergency assistance through voice output, making it particularly beneficial for individuals in remote and undeserved areas. This paper discusses the design, implementation, and evaluation of the system, highlighting its potential to improve healthcare access and outcomes.
Keywords: Health monitoring, SpO2, Respiration rate, Tele-medicine, Machine learning Algorithm.