High performance flexible pressure sensors with tunable piezoresistivity are proposed with percolative composites as single sensing layer using micro-nickel (μNi) wires as conductive filler and polydimethylsiloxane (PDMS) as matrix. The...
Herein, we propose
a highly sensitive
wireless rehabilitation training ball
with a piezoresistive sensor array for patients with Parkinson’s
disease (PD). The piezoresistive material is a low percolation threshold
conductive hydrogel which is formed with polypyrrole (PPy) nanofibers
(NFs) as a conductive filler derived from a polydopamine (PDA) template.
The proton acid doping effect and molecular template of PDA are essential
for endowing PPy NFs with a high aspect ratio, leading to a low percolation
threshold (∼0.78 vol %) and a low Young’s 004Dodulus of
37.69 kPa and hence easy deformation. The piezoresistive sensor exhibited
a static and dynamic stability of 10,000 s and 15,000 cycle times,
respectively. This stability could be attributed to the increased
hydrophilicity of conductive fillers, enhancing the interfacial strength
between the conductive filler and the matrix. The interaction between
the PDA-PPy NFs and the hydrogel matrix endows the hydrogel with toughness
and ensures the stability of the device. Additionally, the microdome
structure of the conductive hydrogel, produced by hot screen-imprinting,
dramatically improves the sensitivity of the piezoresistive sensor
(∼856.14 kPa–1). The microdome conductive
hydrogel can distinguish a subtle pressure of 15.40 Pa compared to
the control hydrogel without a microstructure. The highly sensitive
piezoresistive sensor has the potential to monitor the hand-grip force,
which is not well controlled by patients with PD. The rehabilitation
training ball assembled with a sensor array on the surface and a wireless
chip for communication inside is built and used to monitor the pressure
in real time through the WeChat applet. Thus, this work has significantly
broadened the application of hydrogel-based flexible piezoresistive
sensors for human activity monitoring, which provides a promising
strategy to realize next-generation electronics.
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