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@article{202679,
        author = {Anilkumar N},
        title = {Under the Surface: A Study on Viscoelastic Hysteresis and Structural Material Fault in Smart Footwear},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {7244-7249},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202679},
        abstract = {Modern athletic optimization heavily emphasizes kinetic output and cardiorespiratory metrics, yet the real-time structural degradation of footwear cushioning materials under high-frequency impact remains largely unaddressed. This paper examines the domain of material fatigue and dynamic energy attenuation in elite sports engineering using artificial intelligence. While vis-ible aspects of athlete posture receive substantial attention from computer vision frameworks, the invisible mechanical changes occurring within the mid-sole composite matrix remain criti-cally under-addressed.
The conceptualization of viscoelastic hysteresis drift refers to the progressive loss of energy-return efficiency and structural softening of polymers during prolonged high-intensity compe-tition. Findings indicate that material breakdown operates through dual pathways including compression accumulation and asymmetric structural shearing, both of which contribute to altered biomechanics and elevated injury risk.
By integrating multi-axial pressure-sensing insoles with a Temporal Attention Gated Re-current Unit (TA-GRU), the proposed framework identifies the transition point where footwear cushioning shifts from a protective state into a high-risk degraded condition. The study demon-strates that monitoring material intelligence is not merely an engineering concern but also a critical sports-performance and injury-prevention imperative.},
        keywords = {Viscoelastic Hysteresis, Smart Footwear, Deep Learning, Material Fatigue, Shock Attenuation, Biomechanics, Gated Recurrent Units.},
        month = {May},
        }