Work

Hygiea+: Toward Energy-Efficient and Highly Accurate Toothbrushing Monitoring via Wrist-Worn Gesture Sensing

Year: 2024

Type: article

Source: IEEE Internet of Things Journal

DOI: 10.1109/jiot.2024.3439194

Authors: Xingyu Feng, Chengwen Luo, Junliang Chen, Jianqiang Li, Li Zhang, Zahir Tari, Weitao Xu

Institutions: City University of Hong Kong, Shenzhen Research Institute, Shenzhen University, RMIT University

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, Shenzhen Research Institute, City University of Hong Kong, Government of Shandong Province

Awards: G391925360, G5516222651, G6736814734, G7861906870, G7981627932

OpenAlex ID: W4402261430

FWCI: 0.7

Cites: 45

Cited by: 5

Related to: 10