Signal Decoupling and Readout in Multimodal Sensing: Materials to Algorithms.

Authors

Jiaqing Zhu, Xinan Ma, Chao Rong, Lechen Chen, Wangze Ni, Zeyu Cao, Tao Wang, Bowei Zhang, Fuzhen Xuan

Published in

Small (Weinheim an der Bergstrasse, Germany). Pages e75800. Sep 16, 2026. Epub Sep 16, 2026.

Abstract

Multimodal sensing is increasingly important for next-generation electronic systems, yet multi-physical coupling across materials, devices, and readout chains often compromises signal identifiability. The key challenge is whether coupled observations can be uniquely, stably, and interpretably mapped back to the underlying physical variables. Here, we organize multimodal sensing according to where decisive identifiability is established along the sensing-readout chain, defining three architectures: Partition-Integrated, Continuum-Routed, and Hybrid Co-Decoupling. Partition-Integrated systems establish stimulus-channel correspondence before substantial mixing; Continuum-Routed systems preserve distinguishable signatures within a shared sensing body; and Hybrid Co-Decoupling systems distribute separation across physical encoding, readout, and computation. Representative strategies are compared in terms of mixed-stimulus validation, residual cross-sensitivity, calibration dependence, stability, and generalization. Finally, we highlight opportunities in front-end identifiability, system resilience, and low-power intelligence toward reliable multimodal sensing under realistic operating conditions.

PMID:
42746988
Bibliographic data and abstract were imported from PubMed on 16 Sep 2026.

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