In this work, a conductive composite film composed of multi-walled carbon nanotubes (MWCNTs) and multi-layer Ti3C2Tx MXene nanosheets is used to construct a strain sensor on sandpaper Ecoflex substrate. The composite material forms a sophisticated conductive network with exceptional electrical conductivity, resulting in sensors with broad detection ranges and high sensitivities. The findings indicate that the strain sensing range of the Ecoflex/Ti3C2Tx/MWCNT strain sensor, when the mass ratio is set to 5:2, extends to 240%, with a gauge factor (GF) of 933 within the strain interval from 180% to 240%. The strain sensor has demonstrated its robustness by enduring more than 33,000 prolonged stretch-and-release cycles at 20% cyclic tensile strain. Moreover, a fast response time of 200 ms and detection limit of 0.05% are achieved. During application, the sensor effectively enables the detection of diverse physiological signals in the human body. More importantly, its application in a data glove that is coupled with machine learning and uses the Support Vector Machine (SVM) model trained on the collected gesture data results in an impressive recognition accuracy of 93.6%.
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