There are a few research developments of smart textiles based on various mechanisms, aimed to be not only more flexible for an improved comfortability but also multifunctional, i.e., sensation, perception, or integration 29, 30, 31, 32, 33, 34. Textile as a fundamental part of normal garments has been extensively investigated as a great flexible and stretchable electronics platform 25, 26, 27, 28. In the past few decades, several of flexible devices have been reported with different device structures and materials 22, 23, 24. Motivated by that, substantial efforts have been made for the development of wearable systems equipped with the abovementioned advanced technologies and potential self-sustainability 18, 19, 20, 21. To solve this foreseeing energy crisis issue, energy harvesting technologies and advanced storage devices have emerged to make the waste energy in our surrounding environment valuable. ![]() However, a major bottleneck of the WSNs is the overall power consumption for long-term connectivity of the whole system. Among them, wireless sensor networks (WSNs) have become a key technology to analyze information related to identification, healthcare, human–machine interface (HMI), and human activity monitoring. ![]() With the aid of recent advances in the fifth generation wireless networks and internet of things (IoT), immense widely allocated wearable devices are expected to be wirelessly interconnected at rapid data exchange rates to provide concurrent communication of information about the human body 13, 14, 15, 16, 17. In addition, wearing a few bulky IMUs on human body could cause inevitable interferences to the motions. However, vision recognition by cameras may cause privacy issues, and the utilization of IMUs are not intrinsically flexible and comfortable enough as the preferable wearable solution. When it comes to the continuous and convenient monitoring of diversified human motion states, cameras and inertial measurement unit (IMU) sensors are the widely adopted devices for smart home applications 11, 12. In particular, the detection of the human motions is significantly valuable in creating insights into the user’s health status, activity quantifying, and the establishment of an effective channel between humans and machines 9, 10. To further improve the quality of life, the invention of various wearable sensors based on electrocardiograph 4, electromyogram 5, body temperature 6, heart rate 7, strain sensors 8, etc., offers opportunities in both fitness service and medical diagnostics by the long-term monitoring of physiological signals. Wearable electronics experienced enormous development and advancement in the past decades benefiting from its intrinsically superior flexibility and portability 1, 2, 3. ![]() Toward practical application, we map the physical signals collected through the socks in the virtual space to establish a digital human system for sports monitoring, healthcare, identification, and future smart home applications. ![]() To further address the issue of ineffective analysis methods, an optimized deep learning model with an end-to-end structure on the socks signals for the gait analysis is proposed, which produces a 93.54% identification accuracy of 13 participants and detects five different human activities with 96.67% accuracy. The sock equipped with self-powered functionality also can be used as wearable sensors to deliver information, regarding the identity, health status, and activity of the users. Herein, we developed low-cost triboelectric intelligent socks for harvesting waste energy from low-frequency body motions to transmit wireless sensory data. Current wearable electronics of gait analysis are mainly limited by high fabrication cost, operation energy consumption, or inferior analysis methods, which barely involve machine learning or implement nonoptimal models that require massive datasets for training. Gait reveals sensory information in daily life containing personal information, regarding identification and healthcare. The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable electronics.
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