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Biometric recognition based on scalable end-to-end convolutional neural network using photoplethysmography: A comparative study.
Comput Biol Med
August 2022
Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433, PR China; Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai 200093, China. Electronic address:
Photoplethysmography (PPG), as one of the most widely used physiological signals on wearable devices, with dominance for portability and accessibility, is an ideal carrier of biometric recognition for guaranteeing the security of sensitive information. However, the existing state-of-the-art methods are restricted to practical deployment since power-constrained and compute-insufficient for wearable devices. 1D convolutional neural networks (1D-CNNs) have succeeded in numerous applications on sequential signals.
View Article and Find Full Text PDFThe photosynthetic bacterium Rhodobacter sphaeroides responds to the transition from aerobiosis to anaerobic photosynthesis by increasing the expression of the photosynthesis genes. Mutants have been isolated based on their inability, following such a transition, to increase transcription of the puc operon encoding the apoproteins of the light-harvesting complex II. Mutant D5, a representative of one mutant class, described here, although remaining photosynthetically competent, produced only low levels of the photosynthetic spectral complexes.
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