Compressive Sensing Photoacoustic Imaging Receiver With Matrix-Vector-Multiplication SAR ADC
Wearable photoacoustic imaging devices hold great promise for continuous health monitoring and point-of-care diagnostics. However, the large data volume generated by high-density transducer arrays presents a major challenge for realizing compact and power-efficient wearable systems. This article presents a photoacoustic imaging receiver (RX) that embeds compressive sensing directly into the hardware to address this bottleneck. The RX integrates 16 AFEs and four matrix-vector-multiplication (MVM) SAR ADCs that perform energy- and area-efficient analog-domain compression. The architecture achieves a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\times $</tex-math> </inline-formula>–<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times $</tex-math> </inline-formula> reduction in output data rate while preserving low-loss full-array information. The MVM SAR ADC executes passive and accurate MVM using user-defined programmable ternary weights. Two signal reconstruction methods are implemented: 1) an optimization approach using the fast iterative shrinkage-thresholding algorithm and 2) a learning-based approach employing implicit neural representation. Fabricated in 65-nm CMOS, the chip achieves an ADC’s signal-to-noise-distortion ratio (SNDR) of 57.5 dB at 20.41 MS/s, with an analog front-end (AFE) input-referred noise of 3.5 nV/<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {(\text {Hz})^{1/2}}$</tex-math> </inline-formula>. MVM linearity measurements show <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2} \gt 0.999$</tex-math> </inline-formula> across a wide range of weights and input amplitudes. The system is validated through phantom imaging experiments, demonstrating high-fidelity image reconstruction under up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times $</tex-math> </inline-formula> compression. The RX consumes 5.83 mW/channel and supports a general ternary-weighted measurement matrix, offering a compelling solution for next-generation miniaturized, wearable PA imaging systems.
Authors
- Vivek Boominathan (ORCID: https://orcid.org/0000-0003-4875-3135)
- Huan-Cheng Liao (ORCID: https://orcid.org/0009-0002-0054-9477)
- Yiwei Zou (ORCID: https://orcid.org/0009-0008-2949-5672)
- Ashok Veeraraghavan (ORCID: https://orcid.org/0000-0001-5043-7460)
- Kaiyuan Yang (ORCID: https://orcid.org/0000-0001-7220-9389)
- Lei Li (ORCID: https://orcid.org/0000-0001-6164-2646)
- Yumin Su (ORCID: https://orcid.org/0009-0006-0295-4141)
- Shunyao Zhang (ORCID: https://orcid.org/0000-0002-6227-6905)
- Wei Wang (ORCID: https://orcid.org/0009-0007-4555-564X)
- Arvind Govinday
Institutions
- Rice University (US)
Publication Details
- Journal
- IEEE Journal of Solid-State Circuits
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1109/jssc.2025.3603157
- Primary Topic
- Photoacoustic and Ultrasonic Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00