A Stretchable Strain Sensor Based on CNTs/GR for Human Motion Monitoring

Flexible/stretchable strain sensors have attracted much attention due to their advantages for human-computer interaction, smart wearable and human monitoring. However, there are still great challenges on gaining super durability, quick response, and wide sensing range. This paper provides a simple process to obtain a sensor which is based on graphene (GR)/carbon nanotubes (CNTs) and Ecoflex hybrid, which demonstrates superb endurance (over 1000 cycles at 100% strain), remarkable sensitivity (strain over 125% sensitivity up to 20) and wide sensing range (175%). All results indicate that it is capable for human movement monitoring, such as finger and knee bending and pulse beat. Most importantly, it can be used as a warning function for the night cyclist’s ride. This research provides the feasibility of using this sensor for practical applications.

Through-the-Wall Micro-Doppler De-Wiring Technique via Cycle-Consistent Adversarial Network

The radar penetrating technique has aroused a keen interest in the research community, due to its superior abilities for through-the-wall indoor human motion monitoring. Micro-Doppler signatures in this situation play a significant role in recognition and classification for human activities. However, the live wire buried in the wall introduces additive clutters to the spectrograms. Such degraded spectrograms drastically affect the performance of behind-the-wall human activity detection. In this paper, an ultra-wideband (UWB) radar system is utilized in the through-the-wall scenario to get the feature enhanced micro-Doppler signature called range-max time-frequency representation (R-max TFR). Then, a recently introduced Cycle-Consistent Generative Adversarial Network (Cycle GAN) is employed to realize the end-to-end de-wiring task. Cycle GAN can learn the mapping between spectrograms with and without the live wire effect. To minimize the wiring clutters, a loss function called identity loss is introduced in this work. Finally, the proposed de-wiring approach is evaluated through classification. The results show that the proposed Cycle GAN architecture outperforms other state-of-art de-wiring methods.

A Stretchable and Self-Healing Hybrid Nano-Generator for Human Motion Monitoring

Transparent stretchable wearable hybrid nano-generators present great opportunities in motion sensing, motion monitoring, and human-computer interaction. Herein, we report a piezoelectric-triboelectric sport sensor (PTSS) which is composed of TENG, PENG, and a flexible transparent stretchable self-healing hydrogel electrode. The piezoelectric effect and the triboelectric effect are coupled by a contact separation mode. According to this effect, the PTSS shows a wide monitoring range. It can be used to monitor human multi-dimensional motions such as bend, twist, and rotate motions, including the screw pull motion of table tennis and the 301C skill of diving. In addition, the flexible transparent stretchable self-healing hydrogel is used as the electrode, which can meet most of the motion and sensing requirements and presents the characteristics of high flexibility, high transparency, high stretchability, and self-healing behavior. The whole sensing system can transmit signals through Bluetooth devices. The flexible, transparent, and stretchable wearable hybrid nanogenerator can be used as a wearable motion monitoring sensor, which provides a new strategy for the sports field, motion monitoring, and human-computer interaction.