Abstract
AbstractFunctional triboelectric insoles hold promise for advancing self‐powered wearable technologies. However, their durability is compromised by continuous compressive forces and friction, leading to surface abrasion and material fracturing. To address these challenges, an innovative fabric‐reinforced structure combined with a dual‐L backrest design is developed that enhances anti‐fracture capabilities and electric outputs while enabling AI‐empowered motion monitoring. Polydimethylsiloxane (PDMS) is used as the negative triboelectric material with a dual‐L backrest design, while insulated copper wire (icuW) serves as the positive triboelectric material with an annular structure design. These components are intricately nested to enable a multilayered friction pairing. The fabric‐reinforced structure demonstrates excellent compressive rebound resilience, withstanding forces of at least 1000 N. The functional insole, featuring a fabric‐reinforced dual‐L backrest structure (FRdL‐insole), efficiently harvests biomechanical energy with a peak power of 8214 µW and maintains highly consistent performance after 10 washing cycles and 60 000 durability tests. It can power portable electronic devices such as digital watches, calculators, hygrometers, and LEDs. Enhanced with machine learning algorithms, the FRdL‐insole processes sensor signals to monitor human movements, accurately identifying seven distinct motions. This positions the insole as a smart, real‐time, self‐powered tool for activity recognition, showcasing its potential in intelligent wearable technology.
Published Version
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