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EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing
June 26, 2024, 4:45 a.m. | Shengzhe Lyu, Yongliang Chen, Di Duan, Renqi Jia, Weitao Xu
cs.LG updates on arXiv.org arxiv.org
Abstract: In the realm of smart sensing with the Internet of Things, earable devices are empowered with the capability of multi-modality sensing and intelligence of context-aware computing, leading to its wide usage in Human Activity Recognition (HAR). Nonetheless, unlike the movements captured by Inertial Measurement Unit (IMU) sensors placed on the upper or lower body, those motion signals obtained from earable devices show significant changes in amplitudes and patterns, especially in the presence of dynamic and …
abstract arxiv capability computing context cs.ai cs.hc cs.lg data devices eess.sp human intelligence internet internet of things measurement movements multi realm recognition sensing sensors smart things type usage
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