Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning.
Biomed Phys Eng Express
; 9(2)2023 01 11.
Article
en En
| MEDLINE
| ID: mdl-36596253
ABSTRACT
Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still not straightforward. The best algorithm selection improves the signal-to-noise ratio (SNR) and therefore improves the accuracy of the recognition and classification of vital signs. We recorded more than 300 temporal rPPG signals where the noise was not motion-induced. Then, we investigated the best digital filter in pre-processing temporal rPPG data and compared the performances of 10 filters with 10 orders each (i.e., a total of 100 filters). The performances are assessed using a signal quality metric on three levels. The quality of the raw signals was classified under three categories; Q1 being the best and Q3 being the worst. The results are presented in SNR scores, which show that the Chebyshev II orders of 2nd, 4th, and 6th perform the best for denoising rPPG signals.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Fotopletismografía
Idioma:
En
Revista:
Biomed Phys Eng Express
Año:
2023
Tipo del documento:
Article
País de afiliación:
Turquía