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Deep-learning-assisted printed liquid metal sensory system for wearable applications and boxing training.
- Source :
- NPJ Flexible Electronics; 8/8/2023, Vol. 7 Issue 1, p1-10, 10p
- Publication Year :
- 2023
-
Abstract
- Liquid metal (LM) exhibits a distinct combination of high electrical conductivity comparable to that of metals and exceptional deformability derived from its liquid state, thus it is considered a promising material for high-performance soft electronics. However, rapid patterning LM to achieve a sensory system with high sensitivity remains a challenge, mainly attributed to the poor rheological property and wettability. Here, we report a rheological modification strategy of LM and strain redistribution mechanics to simultaneously simplify the scalable manufacturing process and significantly enhance the sensitivity of LM sensors. By incorporating SiO<subscript>2</subscript> particles into LM, the modulus, yield stress, and viscosity of the LM-SiO<subscript>2</subscript> composite are drastically enhanced, enabling 3D printability on soft materials for stretchable electronics. The sensors based on printed LM-SiO<subscript>2</subscript> composite show excellent mechanical flexibility, robustness, strain, and pressure sensing performances. Such sensors are integrated onto different locations of the human body for wearable applications. Furthermore, by integrating onto a tactile glove, the synergistic effect of strain and pressure sensing can decode the clenching posture and hitting strength in boxing training. When assisted by a deep-learning algorithm, this tactile glove can achieve recognition of the technical execution of boxing punches, such as jab, swing, uppercut, and combination punches, with 90.5% accuracy. This integrated multifunctional sensory system can find wide applications in smart sport-training, intelligent soft robotics, and human-machine interfaces. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 23974621
- Volume :
- 7
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- NPJ Flexible Electronics
- Publication Type :
- Academic Journal
- Accession number :
- 169825632
- Full Text :
- https://doi.org/10.1038/s41528-023-00272-1