Multi-attribute wearable pressure sensor based on multilayered modulation with high constant sensitivity over a wide range

Ning Li, Song Gao, Yang Li*, Jianwen Liu, Wenhao Song, Guozhen Shen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

Flexible pressure sensors capable of monitoring diverse physiological signals and body movements have garnered tremendous attention in wearable electronic devices. Thereinto, high constant sensitivity over a wide pressure range combined with breathability, biocompatibility, and biodegradability is pivotal for manufacturing of reliable pressure sensors in practical sensing applications. In this work, inspired by the multilayered structure of skin epidermis, we propose and demonstrate a multi-attribute wearable piezoresistive pressure sensor consisting of multilayered gradient conductive poly(ε-caprolactone) nanofiber membranes composites. In response to externally applied pressure, a layer-by-layer current path is activated inside the multilayered membranes composites, leading to the most salient sensing performance of high constant sensitivity of 33.955 kPa−1 within the pressure range of 0–80 kPa. The proposed pressure sensor also exhibits a fast response—relaxation time, a low detection limit, and excellent stability, which can be successfully used to measure human physiological signals. Lastly, an integrated sensor array system that can locate objects’ positions is constructed and applied to simulate sitting posture monitoring. These results indicate that the proposed pressure sensor holds great potential in health monitoring and wearable electronic devices. [Figure not available: see fulltext.]

Original languageEnglish
Pages (from-to)7583-7592
Number of pages10
JournalNano Research
Volume16
Issue number5
DOIs
Publication statusPublished - May 2023

Keywords

  • high constant sensitivity
  • multi-attribute
  • multilayer structure
  • physiological signals monitoring
  • wearable pressure sensors

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