Abstract

Owing to the flexibility, lightweight, long-life and low cost, polymers are promising candidates to realize electromechanical conversion in wearable electronics. The flexoelectric effect enables non-piezoelectric materials to achieve electromechanical coupling, thereby broadening application ranges of nonpolar polymers. In this work, the porous samples of polydimethylsiloxane (PDMS) with various pore sizes and porosities are fabricated by the sacrificial salt template method and the chemical gas foaming method. The flexoelectric polarization response can be tuned directly by the structural characters of the porous PDMS. The transverse flexoelectric coefficient of porous PDMS can reach approximately 2.9 times the counterpart of the bulk one. The competitive mechanism between strain gradient and permittivity is proposed on flexoelectricity of random porous media by dielectric impedance spectrums and finite element analyses. The present regulation of flexoelectricity provides an alternative to electromechanical conversion. With the deep learning technique based on one-dimensional convolution neural networks, actions of both sick and normal legs of various stroke patients can be well recognized by the designed device of rehabilitation. The present rehabilitation monitoring system, which is an innovative application of the flexoelectricity in the porous polymers, offers a new approach to support physical therapy for post-stroke patients.

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