Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

• Published in: Npj flexible electronics Vol. 4; no. 1; pp. 1 - 12
• Main Authors: Zhang, Zixuan, He, Tianyiyi, Zhu, Minglu, Sun, Zhongda, Shi, Qiongfeng, Zhu, Jianxiong, Dong, Bowei, Yuce, Mehmet Rasit, Lee, Chengkuo
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 26.10.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/987; 639/301/1005; Artificial intelligence; Chemistry and Materials Science; Cost analysis; Deep learning; Electronics; Electronics and Microelectronics; Energy consumption; Energy harvesting; Gait; Health care; Instrumentation; Internet of Things; Machine learning; Massive data points; Materials Science; Optical and Electronic Materials; Polymer Sciences; Smart buildings; Virtual reality; Wearable technology

The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable electronics. Gait reveals sensory information in daily life containing personal information, regarding identification and healthcare. Current wearable electronics of gait analysis are mainly...