Evaluation of biases in remote photoplethysmography methods
Ananyananda Dasari; Sakthi Kumar Arul Prakash; László A. Jeni; Conrad S. Tucker · 2021 · npj Digital Medicine
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
This work investigates the estimation biases of remote photoplethysmography (rPPG) methods for pulse rate measurement across diverse demographics. Advances in photoplethysmography (PPG) and rPPG methods have enabled the development of contact and noncontact approaches for continuous monitoring and collection of patient health data. The contagious nature of viruses such as COVID-19 warrants noncontact methods for physiological signal estimation. However, these approaches are subject to estimation biases due to variations in environmental conditions and subject demographics. The performance of c
Abstract by Ananyananda Dasari; Sakthi Kumar Arul Prakash; László A. Jeni; Conrad S. Tucker, npj Digital Medicine (2021) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1038/s41746-021-00462-z