ADVANCED PIEZOELECTRIC SENSORS INTEGRATED WITH AI FOR REAL-TIME MEDICAL IMAGING

Piezoelectric sensors have proved to be effective in medical diagnostics and imaging because of the inbuilt ability of the equipment to sense mechanical power into highly sensitive as well as high quality electrical signals for the past few years. Artificial intelligence (AI) based sensors are rapidly transforming real-time medical imaging since they offer automatic information retrieval, enhance the number of signals captured, and enable early disease detection. Piezoelectric nanogenerators (PENGs) and ultrasonic transducers are already connected to machine learning (ML) algorithms and deep learning models to process multifaceted biomechanical images in real-time and improve the quality of diagnosing and do away with the use of traditional imaging modalities. The case study focuses on the recent experience with piezoelectric sensor technology, its integration with AI to offer real-time medical images, its functionality, in what ways it is used, and what problems are associated with it. The potential of these systems in development to achieve complete autonomy, independent, and clinically proven medical imaging systems is also addressed..