Abstract
In recent years, the prevalence of cardiovascular diseases has been growing geometrically, especially among the elderly. Real-time heart rate monitoring becomes an effective measure for preventing cardiovascular diseases. Traditional contact-based real-time heart rate measurement methods require long-term wearing of contact electrodes, which can cause inconvenience to the elderly population. In this study, a wide spectrum full color night vision elderly face video heart rate automatic measurement and early warning system was designed and developed by combining imaging photoplethysmography (IPPG), video acquisition equipment based on starlight wide spectrum camera and high-speed face recognition signal processing algorithm based on deep learning. By constructing a software and hardware platform, a comprehensive evaluation of the system’s application in elderly facial video heart rate measurement experiments was conducted.
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