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What is rPPG Techniques for Indonesian Subjects about?

This study evaluates the performance of various remote photoplethysmography (rPPG) algorithms on an Indonesian dataset to improve non-contact vital sign monitoring. The research identifies the Plane Orthogonal to Skin (POS) algorithm as the most effective, achieving a Mean Absolute Error (MAE) of 2.59 and a Root Mean Square Error (RMSE) of 4.65. The findings aim to address the underrepresentation of Indonesian subjects in rPPG research and enhance the accuracy of non-contact heart rate measurements in diver

Author

tariz darin

Language

EN