CAREER: A Signal Encoding and Decoding Framework for Photoacoustic System Miniaturization: From Theory to Applications

About This Grant

Wearable medical imaging devices capable of continuously monitoring health in daily life will significantly advance healthcare. Traditional medical imaging equipment, although powerful, tends to be bulky, expensive, and energy-intensive, limiting its accessibility and usability. This innovative research proposes to miniaturize a photoacoustic imaging (PAI) system—a promising technology combining ultrasound and light—to visualize deep tissue functions. By developing a novel signal encoding and decoding framework, the hundreds of detection channels needed in conventional PAI can be drastically reduced to just one. This advance makes it possible to create lightweight, affordable, and energy-efficient wearable imaging devices. Such devices will greatly benefit telemedicine, enhance early diagnosis and timely intervention of diseases, particularly in underserved and remote communities, and ultimately contribute to better patient outcomes. Additionally, the project incorporates educational activities designed to inspire undergraduate and high-school students to pursue careers in medical device innovation and STEM fields. The technical goal of this CAREER project is to develop a novel spatiotemporal signal encoding and decoding framework enabling the miniaturization of PAI. Conventional PAI requires arrays of hundreds to thousands of ultrasonic detectors for high-resolution imaging, resulting in large, expensive, and power-hungry equipment. To overcome these limitations, the project will implement a specialized encoding medium (hardware) to uniquely tag photoacoustic waves with distinct spatiotemporal signatures, enabling serial detection by a single-element detector. Along with this hardware innovation, a mathematical decoding algorithm (software) will be developed to reconstruct the original signals, effectively creating over one thousand virtual detection channels from a single physical detector. This integrated hardware-software approach will maintain imaging performance comparable to traditional multi-detector systems while dramatically reducing the device size, cost, and energy consumption by one to two orders of magnitude. Successful completion of this research will provide foundational knowledge for designing compact and efficient wearable PAI and ultrasound devices, promising wearable applications for clinical diagnostics and healthcare delivery. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.