| Author: | So, Pak Hei |
| Title: | Fabrication of ultra-durable and highly sensitive soft strain sensor with wide working range using MWCNT/AgNW hybrid network and acoustic field optimization: application in exoskeleton feedback control |
| Advisors: | Cheung, Chung Wai James (BME) |
| Degree: | M.Phil. |
| Year: | 2025 |
| Department: | Department of Biomedical Engineering |
| Pages: | xvii, 130 pages : color illustrations |
| Language: | English |
| Abstract: | The increasing prevalence of disabilities, driven by aging populations and conditions like stroke, underscores the urgent need for advanced assistive technologies. Traditional exoskeletons, though effective, are often rigid, heavy, and lack adaptability, compromising user comfort and mobility. Soft exoskeletons offer a compelling alternative, providing flexibility and natural movement mimicry. Their success, however, depends on integrating highly sensitive, durable, and stretchable strain sensors for precise feedback control. This research introduces a groundbreaking soft strain sensor based on a hybrid network of multi-walled carbon nanotubes (MWCNTs) and silver nanowires (AgNWs), fabricated using an optimized ultrasonic-assisted method, tailored for a tendon-driven exoskeleton glove. The hybrid network leverages the unique strengths of MWCNTs and AgNWs. MWCNTs contribute mechanical robustness and stretchability due to their high aspect ratio, while AgNWs enhance electrical conductivity, ensuring exceptional sensitivity. This synergy yields a sensor with a gauge factor (GF) of 74.829, a working range up to 240% strain, and durability exceeding 15,000 cycles at 100% strain—metrics that outperform many conventional soft strain sensors, which often sacrifice sensitivity for stretchability or vice versa. The ultrasonic fabrication process, optimized for duration and power, ensures uniform dispersion of nanomaterials within the Ecoflex substrate, creating a stable conductive network. This cost-effective, scalable method uses ultrasonication’s high-energy jets to bond nanomaterials effectively, enhancing sensor reliability. Environmental stability is a critical aspect of this sensor’s performance, particularly under varying temperature and humidity conditions. Testing revealed that the sensor maintains consistent sensitivity and durability across a temperature range of -10°C to 50°C and relative humidity levels from 20% to 90%. At elevated temperatures (e.g., 50°C), the sensor’s GF remained stable, with only a 2% variation, attributed to the thermal resilience of the MWCNT/AgNW network. In high-humidity environments (90% RH), the Ecoflex substrate’s hydrophobic properties minimized moisture ingress, preserving electrical conductivity and preventing degradation over 10,000 cycles. Conversely, at low temperatures (-10°C), the sensor retained flexibility and a GF above 70, demonstrating robustness against brittleness—a common issue in polymer-based sensors. These results highlight the sensor’s suitability for real-world applications, where environmental fluctuations are inevitable. Integrated into a tendon-driven exoskeleton glove, the sensor enables precise real-time feedback, accurately interpreting user movements for rehabilitation purposes. Compared to existing technologies, it excels in sensitivity for detecting subtle motions, a wide strain range for full-body movements, and durability under repeated stress. Future research will focus on clinical trials with stroke survivors to validate performance in practical settings and address scalability challenges. Scaling the ultrasonic fabrication process for mass production while maintaining quality and cost-efficiency remains a hurdle, yet its simplicity offers a promising pathway for widespread adoption in healthcare. In conclusion, this study advances soft strain sensor technology by delivering a highly sensitive, durable, and environmentally stable solution for exoskeleton feedback control. The MWCNT/AgNW hybrid, paired with ultrasonic fabrication, meets the rigorous demands of assistive devices, with robust performance across diverse environmental conditions paving the way for future innovations in rehabilitation. |
| Rights: | All rights reserved |
| Access: | open access |
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