S. Kumar, W. Glenewinkel, A. Singh
Texas A&M University,
United States
Keywords: artificial intelligence, healthcare, health monitoring, internet of things, privacy
Summary:
Artificial Intelligence (AI) is revolutionizing manufacturing across industries, enabling innovative products and streamlined processes. This paper presents a case study on the design, production, and deployment of a remote AI-enabled stethoscope, highlighting how AI-driven manufacturing enhances efficiency, quality, and accessibility in medical device production. By addressing challenges like scalability, precision, and regulatory compliance, this case study showcases the integration of AI and advanced manufacturing technologies. In this talk, we present the ongoing design, development, and manufacturing of an AI-powered stethoscope being developed by Logicboots, India, and being secured by researchers at Texas A&M University. We also present the AI, security, and privacy design aspects of this product. The device aims to revolutionize healthcare by providing real-time cardiac and pulmonary diagnostics from remote locations. Using AI algorithms for sound analysis and anomaly detection, the device combines advanced acoustic sensors, AI, and IoT connectivity to identify conditions like murmurs, arrhythmias, and respiratory irregularities with high accuracy. IoT connectivity enables secure real-time data transmission to cloud platforms for remote monitoring and integration with electronic health records (EHRs). Its affordability and user-friendly design make it accessible for clinics, telemedicine, home healthcare, and emergency response, particularly in underserved regions. The manufacturing process incorporates Industry 4.0 principles, including smart production lines, predictive maintenance, and digital twins, to optimize efficiency and minimize defects. AI-powered computer vision systems enforce stringent quality control, while generative design algorithms produce ergonomic and durable components tailored to diverse user needs. Machine learning (ML) models automate sensor calibration, improving accuracy and accelerating production timelines. Additionally, AI-enabled predictive analytics streamline supply chain management, reducing waste and ensuring timely component procurement. Security and privacy are paramount for AI-enabled healthcare devices. Robust data encryption and secure transmission mechanisms protect patient information during remote diagnostics, adhering to frameworks like GDPR and HIPAA. Privacy-enhancing technologies and de-identified training datasets safeguard patient confidentiality and prevent exposure of personally identifiable information (PII). These measures foster trust in AI-driven healthcare while ensuring compliance with medical regulations, such as ISO 13485 and HIPAA. Currently in trial in India, the AI stethoscope addresses challenges like regulatory compliance, false positives, and connectivity in remote areas. Future enhancements include wearable integrations, expanded disease detection capabilities, and global deployment, positioning this device as a transformative solution for preventive healthcare. By merging advanced manufacturing technologies with AI capabilities, this study underscores the potential of AI in creating smarter, secure, and sustainable production systems, setting a blueprint for innovation in intelligent medical devices.