Multifunctional conductive hydrogel based on carboxymethyl cellulose/oxidized sodium alginate for machine learning-guided sports training

Clinical Snapshot

Key Findings

• P Value: Not reported

• Effect Size: High mechanical toughness (2416 kJ/m³) and stretchability (1829%)

• Primary Outcome: Machine learning validation accuracy of 98.75% for movement technique assessment

• Nnt Or Sensitivity: Gauge factor up to 2.53 with multi-range sensitivity

• Confidence Interval: Not reported

Clinical Application

High feasibility for integration into wearable devices, though manufacturing scalability unclear Relevant for Australian sports medicine and physiotherapy practices, potential TGA medical device classification required for clinical applications Athletes, fitness enthusiasts, and individuals requiring continuous movement monitoring

Abstract

Multifunctional hydrogels have shown great promise in advanced wearable sensing technologies; however, their performance under real-world sweaty and dynamic conditions remains a significant challenge. In this study, a highly conductive and adhesive hydrogel was developed using poly(AM-co-AA), carboxymethyl cellulose (CMC), oxidized sodium alginate (OSA), and polydopamine-modified carbon nanotubes (PDA-CNT). Featuring a dual dynamic cross-linking system based on reversible Schiff base bonds and strong hydrogen bonding, the hydrogel demonstrates high mechanical toughness (2416 kJ/m3), excellent stretchability (1829%), and stable electrical conductivity (1.5 S/m). It exhibits outstanding sweat resistance, maintaining strong adhesion and reliable sensing performance even during intense physical activities, along with high fatigue resistance over 10,000 deformation cycles, enabling long-term reliable monitoring. As a highly sensitive strain sensor, it offers multi-range gauge factors (up to 2.53) and accurately captures human motion and physiological signals without interference from sweat or motion artifacts. When integrated with machine learning algorithms, the sensor achieves a validation accuracy of 98.75%, providing real-time feedback on movement techniques and supporting personalized training optimization. Furthermore, the hydrogel demonstrates significant antibacterial properties and good biocompatibility, making it an ideal candidate for next-generation wearable electronic devices suited for long-term athletic training and high-sweat environments.

References

1. 1.Li, Z., Ge, R., Li, N., Hou, J., Zhao, Z., Hua, J., Du, C., & Wang, L. (2026). Multifunctional conductive hydrogel based on carboxymethyl cellulose/oxidized sodium alginate for machine learning-guided sports training. Carbohydrate Polymers. https://doi.org/10.1016/j.carbpol.2026.124942