Randomized trial demonstrates high linearity in flexible pressure sensors, indicating advancements in wearable health monitoring.
Flexible pressure sensors with a porous architecture are highly desirable for wearable health monitoring and intelligent human–machine interaction, owing to their excellent comfort and conformability to human motion. However, conventional porous sensors often suffer from poor signal accuracy and unstable output, which limit their capability for precision sensing. To address these challenges, we designed and fabricated a flexible pressure sensor with exceptional linearity by mimicking the unique surface structure of Iron Cross Begonia (Begonia masoniana) leaves. The sensor is constructed using a readily available melamine foam as the backbone: a porous sensing scaffold is first obtained via a simple dip-coating process, and a film featuring bioinspired protrusions is fabricated by repeated replica molding. Lamination of these two components yields a stacked sensor device. Characterization demonstrates that the sensor achieves a broad pressure detection range of up to 350 kPa, with a minimum resolvable pressure of 250 Pa, and exhibits an excellent linearity of 0.999 over its entire working range (0–350 kPa). Moreover, the sensor shows stable responses under varying loading frequencies, is capable of detecting low-frequency signals, and retains its performance without notable degradation even after 5000 repeated loading-unloading cycles. In practical applications, the sensor accurately monitors flexion and extension movements of the wrist, finger, neck, and knee, capturing human motion signals with high fidelity. Furthermore, it enables information encoding and transmission through finger gestures. The proposed bioinspired structural design strategy effectively enhances the overall performance of porous pressure sensors, offering a new paradigm for the development of flexible sensing devices with promising applications in wearable health monitoring, human motion detection, and human–machine interaction.
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Chen et al. (2026) studied this question.
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