Table 1 Technology Readiness Level (TRL) of fiber-based soft systems
From: Advances and perspectives in fiber-based electronic devices for next-generation soft systems
Device type | TRL range | Demonstration environment | Mass production readiness | Improvement strategy |
|---|---|---|---|---|
3–6 | Lab-scale prototypes; Wearable, HMI, and soft robotic applications | Partially compatible with textile manufacturing; most remain at research-level scalability | Material encapsulation, hybrid sensing, structural design, Machine learning-based signal correction | |
4–6 | Lab-scale devices; Wearable and industrial safety demos | Moderate; scalable with thermal drawing process, but further process control needed | Thermal conductivity enhancement, encapsulation of moisture barrier, hybrid composites | |
3–5 | Lab-scale devices; Wearable, implantable, and industrial safety applications | Limited; Stability and reproducibility need improvement | Enzyme stabilization, molecularly imprinted polymer optimization, humidity control | |
3–6 | Research-grade device; In vivo neural recoding and wearable EMG/ECG/EEG systems, skin electronics | Moderate; Long-term stability and biocompatibility remain challenging | Biocompatible materials and coating, interfacial impedance reduction, Algorithm for real-time signal analysis | |
4–6 | Early-stage prototype; Wearable applications | Moderate; Mass production demonstrated in select studies | Durable structure for preventing leakage, material optimization, development of complex generation mechanism | |
3–5 | Lab-scale prototype; Integrated smart textile system | Limited; Stability and leakage prevention need improvement | Materials optimization, improvement of electrode structure, implementation of thermal runaway mitigation system | |
4–6 | Pre-commercial prototype; Wearable demos and display-integrated system | Good; Ready for industrial adoption | Spectral tunability, enhancement of mechanical durability | |
4–6 | Lab-scale prototype; Soft robotic systems and artificial muscles application | Limited; mass production due to challenges in driven source control | Stable Joule heating design, Machine learning-based feedback control, Improvement of work capacity and accuracy | |
4–6 | Lab-scale device; In vivo neural interface and stimulation, | Moderate; Manual or small-scale fabrication processes for most cases, with some studies enabling mass production | Enhancement of charge injection capacity (CIC), Standardization, and systematic establishment of stimulation condition |
