4.6 Article

Flexible, Highly Sensitive, and Ultrafast Responsive Pressure Sensor with Stochastic Microstructures for Human Health Monitoring

Journal

ADVANCED ENGINEERING MATERIALS
Volume 23, Issue 2, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adem.202000902

Keywords

abrasive paper; flexible pressure sensor; human health monitoring; stochastic microstructures; thermoplastic polyurethane

Funding

  1. National Natural Science Foundation of China [61701488, 62074145]
  2. Shenzhen Basic Research Plan [JCYJ20170818162548196, JCYJ20180507182530279]
  3. National key R&D Project from Minister of Science and Technology of China [2016YFA0202702]
  4. Youth Innovation Promotion Association of the Chinese Academy of Sciences [2017411]

Ask authors/readers for more resources

Flexible and wearable sensors made from TPU with unique surface morphology inspired by skin epidermis show high sensitivity, ultrafast response time, low detection limits, and excellent cycling stability, making them promising for human health monitoring applications.
Flexible and wearable sensors are now becoming the favorite of the new information age for their great prospects, especially in human health monitoring, and which are mainly aimed at improving the comprehensive sensing performance. However, the equilibrium between sensitivity and response time of the sensor has not been well balanced. Herein, a simple and low-cost strategy to fabricate flexible pressure sensors based on thermoplastic polyurethane (TPU) substrate with unique surface stochastic morphology replicated from the abrasive paper, which is inspired by skin epidermis, is presented. The integrated TPU flexible pressure sensor exhibits a high sensitivity of -2.24 kPa(-1) in a linear pressure regime of 0-200 Pa, and the effective working range of this sensor is close to 2 kPa, ultrafast response time and relaxation time of 10 ms, low detection limits of 0.72 Pa, and excellent cycling stability over 3000 cycles. The fabricated sensors demonstrate outstanding sensing capabilities in monitoring human physiological signals, such as subtle pulse, wrist movement, and speech recognition, making promising potential in practical human health monitoring applications.

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