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Evaluation of video-based rPPG in challenging environments: Artifact mitigation and network resilience.
Nguyen, Nhi; Nguyen, Le; Li, Honghan; Bordallo López, Miguel; Álvarez Casado, Constantino.
Afiliación
  • Nguyen N; Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland. Electronic address: thi.tn.nguyen@oulu.fi.
  • Nguyen L; Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland. Electronic address: le.nguyen@oulu.fi.
  • Li H; Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland; Division of Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan. Electronic address: lihonghan@mbm.me.es.osaka-u.ac.jp.
  • Bordallo López M; Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland; VTT Technical Research Center of Finland Ltd., Oulu, Finland. Electronic address: miguel.bordallo@oulu.fi.
  • Álvarez Casado C; Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland. Electronic address: constantino.alvarezcasado@oulu.fi.
Comput Biol Med ; 179: 108873, 2024 Sep.
Article en En | MEDLINE | ID: mdl-39053334
ABSTRACT
Video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact vital sign monitoring, especially under controlled conditions. However, the accurate measurement of vital signs in real-world scenarios faces several challenges, including artifacts induced by videocodecs, low-light noise, degradation, low dynamic range, occlusions, and hardware and network constraints. In this article, a systematic and comprehensive investigation of these issues is conducted, measuring their detrimental effects on the quality of rPPG measurements. Additionally, practical strategies are proposed for mitigating these challenges to improve the dependability and resilience of video-based rPPG systems. Methods for effective biosignal recovery in the presence of network limitations are detailed, along with denoising and inpainting techniques aimed at preserving video frame integrity. Compared to previous studies, this paper addresses a broader range of variables and demonstrates improved accuracy across various rPPG methods, emphasizing generalizability for practical applications in diverse scenarios with varying data quality. Extensive evaluations and direct comparisons demonstrate the effectiveness of these approaches in enhancing rPPG measurements under challenging environments, contributing to the development of more reliable and effective remote vital sign monitoring technologies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Grabación en Video / Artefactos / Fotopletismografía Límite: Adult / Female / Humans / Male Idioma: En Revista: Comput Biol Med Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Grabación en Video / Artefactos / Fotopletismografía Límite: Adult / Female / Humans / Male Idioma: En Revista: Comput Biol Med Año: 2024 Tipo del documento: Article
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