<p>Conductive hydrogel-based strain sensors, as key components of electronic skins, have garnered significant attention for the development of advanced human-machine interfaces and flexible electronics. However, their intrinsic limitations of large hysteresis and poor mechanical robustness pose significant challenges for achieving the high accuracy and long-term stability required for advanced sensing systems. Here, we achieve hysteresis suppression and structural stability by constructing a microphase-separated interlocking network within a 3D-printable poly(vinyl alcohol) (PVA)/conductive carbon black (CCB) hydrogel. The resulting conductive hydrogel strain sensor possesses low electrical hysteresis (0.82%) and high cycle stability (&gt;1×10⁴ cycles), enabling real-time and precise monitoring of joint bending and muscle contraction. By converting finger motion into machine-learnable signal patterns, the sensor enables an identification system that decodes continuous strain signals into alphabetical information, offering a novel human-machine interaction modality. This work provides a promising conductive hydrogel platform with enhanced sensing fidelity and interaction capability towards intelligent human-machine interactions.</p>