Cargando…
Assessment of Non-Invasive Blood Pressure Prediction from PPG and rPPG Signals Using Deep Learning †
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP) measurement is interesting for various reasons. First, PPG can easily be measured using fingerclip sensors. Second, camera based approaches allow to derive remote PPG (rPPG) signals similar to PPG and therefore provid...
Autores principales: | Schrumpf, Fabian, Frenzel, Patrick, Aust, Christoph, Osterhoff, Georg, Fuchs, Mirco |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472879/ https://www.ncbi.nlm.nih.gov/pubmed/34577227 http://dx.doi.org/10.3390/s21186022 |
Ejemplares similares
-
Assessment of ROI Selection for Facial Video-Based rPPG
por: Kim, Dae-Yeol, et al.
Publicado: (2021) -
Remote heart rate monitoring - Assessment of the Facereader rPPg by Noldus
por: Benedetto, Simone, et al.
Publicado: (2019) -
Local attention and long-distance interaction of rPPG for deepfake detection
por: Wu, Jiahui, et al.
Publicado: (2023) -
GRGB rPPG: An Efficient Low-Complexity Remote Photoplethysmography-Based Algorithm for Heart Rate Estimation
por: Haugg, Fridolin, et al.
Publicado: (2023) -
Two-Stage Motion Artifact Reduction Algorithm for rPPG Signals Obtained from Facial Video Recordings
por: Abdulrahaman, Luqman Qader
Publicado: (2023)