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eess.SP2024
CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition
Mengxi Liu, Zimin Zhao, Daniel GeiÃler +3
Recent advancements in Artificial Neural Networks have significantly improved human activity recognition using multiple time-series sensors. While employing numerous sensors with h…
eess.SP2024
iMove: Exploring Bio-impedance Sensing for Fitness Activity Recognition
Mengxi Liu, Vitor Fortes Rey, Yu Zhang +3
Automatic and precise fitness activity recognition can be beneficial in aspects from promoting a healthy lifestyle to personalized preventative healthcare. While IMUs are currently…
eess.SP2024
Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition
Si Zuo, Vitor Fortes Rey, Sungho Suh +2
Human activity recognition (HAR) from on-body sensors is a core functionality in many AI applications: from personal health, through sports and wellness to Industry 4.0. A key prob…