A soft-voting ensemble of SVM, decision tree, and MLP classifies six sitting postures plus standing from Azure Kinect joint angles with 98.1% F1 on a new 33,409-sample dataset.
Associations of sedentary time and physical activity with adverse health conditions: Outcome- wide analyses using isotemporal substitution model,
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SitPose: Real-Time Detection of Sitting Posture and Sedentary Behavior Using Ensemble Learning With Depth Sensor
A soft-voting ensemble of SVM, decision tree, and MLP classifies six sitting postures plus standing from Azure Kinect joint angles with 98.1% F1 on a new 33,409-sample dataset.