Bioinspired Low‐Power Mechanical Sensing Technologies

ABSTRACT Bioinspired low‐power mechanical sensing technology offers a promising solution to address the escalating energy consumption challenges faced by conventional sensing systems. Traditional mechanical sensing architectures, relying on dense sensor arrays and continuous data acquisition, suffer from substantial power consumption and limited long‐term deployability. In contrast, biological mechanosensory systems achieve high sensitivity, robustness, and adaptive intelligence with minimal energy expenditure through structure‐enabled signal acquisition, efficient neural processing, and closed‐loop actuation. Accordingly, this article evaluates recent advances across the entire bioinspired mechanical sensing pipeline, encompassing signal acquisition, processing, and actuation. At the acquisition frontier, bioinspired sensing strategies based on web‐like, slit‐organ, lever‐based, and skin‐inspired topologies are reviewed, illustrating how structural amplification, intrinsic filtering, and directional selectivity enable efficient signal capture with ultralow energy overhead. Building upon these front‐end mechanisms, low‐power signal processing strategies inspired by biological nervous systems are discussed, emphasizing efficient signal transduction and event‐driven, neuromorphic computation to mitigate redundant data handling. Subsequently, biological actuation mechanisms and their engineered counterparts are summarized, highlighting sensorimotor coupling and closed‐loop feedback as critical routes to further energy optimization. Finally, representative applications in healthcare and environmental monitoring are presented, alongside current challenges and future trajectories, providing a comprehensive framework for developing next‐generation mechanical sensing platforms.

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Publication Details

Journal
Advanced Materials
Published
2026-09-22
DOI
https://doi.org/10.1002/adma.75090
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
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article

Bioinspired Low‐Power Mechanical Sensing Technologies

Xiancun Meng, Shichao Niu, Xingkai Huang, Guangjun Chen et al.
Advanced Materials
Advanced Sensor and Energy Harvesting Materials
article

Bioinspired Low‐Power Mechanical Sensing Technologies

Xiancun Meng, Shichao Niu, Xingkai Huang, Guangjun Chen, Changchao Zhang, Bo Li, You Chen, Zhiwu Han, Xiangxiang Zhang, Xueping Zhang, Luquan Ren, Junqiu Zhang
article en

Abstract

ABSTRACT Bioinspired low‐power mechanical sensing technology offers a promising solution to address the escalating energy consumption challenges faced by conventional sensing systems. Traditional mechanical sensing architectures, relying on dense sensor arrays and continuous data acquisition, suffer from substantial power consumption and limited long‐term deployability. In contrast, biological mechanosensory systems achieve high sensitivity, robustness, and adaptive intelligence with minimal energy expenditure through structure‐enabled signal acquisition, efficient neural processing, and closed‐loop actuation. Accordingly, this article evaluates recent advances across the entire bioinspired mechanical sensing pipeline, encompassing signal acquisition, processing, and actuation. At the acquisition frontier, bioinspired sensing strategies based on web‐like, slit‐organ, lever‐based, and skin‐inspired topologies are reviewed, illustrating how structural amplification, intrinsic filtering, and directional selectivity enable efficient signal capture with ultralow energy overhead. Building upon these front‐end mechanisms, low‐power signal processing strategies inspired by biological nervous systems are discussed, emphasizing efficient signal transduction and event‐driven, neuromorphic computation to mitigate redundant data handling. Subsequently, biological actuation mechanisms and their engineered counterparts are summarized, highlighting sensorimotor coupling and closed‐loop feedback as critical routes to further energy optimization. Finally, representative applications in healthcare and environmental monitoring are presented, alongside current challenges and future trajectories, providing a comprehensive framework for developing next‐generation mechanical sensing platforms.

Advanced Materials
Jilin University (CN), Liaoning Academy of Materials
Affordable and clean energy
Openalex Percentile: Top 21%
Advanced Sensor and Energy Harvesting Materials
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