A research team at the Korea Advanced Institute of Science and Technology (KAIST) has developed an e-textile platform capable of capturing soldiers’ motion and vital signs in real time. The system combines direct ink writing (DIW) with high-performance functional materials and has been tested under real military conditions. The aim is to enable personalized training scenarios while ensuring cost-effective mass production.
What sets this platform apart is the direct integration of electronic components—such as sensors and electrodes—into textiles. Conductive inks are printed in defined patterns directly onto fabrics, such as uniforms or gloves. One of the substrates used is a styrene-butadiene-styrene (SBS) copolymer, which provides mechanical flexibility. Electrical conductivity is achieved through embedded multiwalled carbon nanotubes (MWCNTs). The sensors can stretch up to 102% and maintain stable performance even after 10,000 load cycles.
Major Kyusoon Pak stated, “Our military is currently facing both a crisis and an opportunity due to the decrease in military personnel resources caused by the demographic cliff and the advancement of science and technology. Also, respect for life in the battlefield is emerging as a significant issue. This research aims to secure original technology that can provide customized training according to military branch/duty and type of combat, thereby enhancing the combat power and ensuring the survivability of our soldiers.”
The team also developed conductive inks based on silver flakes and polystyrene to enable vertical interconnects between textile layers. These so-called interconnect electrodes support the creation of multilayered e-textile systems with high functional density. In field tests, sensors were placed on shoulder, knee, and elbow areas to record body movements during various exercises in real time.
He added, “I hope this research will be evaluated as a case that achieved both scientific contribution and military applicability.”
Beyond motion analysis, the researchers also demonstrated applications such as tracking breathing patterns via a smart mask and object recognition using machine learning integrated into gloves. By combining materials science, additive manufacturing, and data analysis, the technology aims to enhance both efficiency and safety in military operations over the long term.
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