The dataset of photoplethysmography signals collected from a pulse sensor to measure blood glucose level

Non-invasive monitoring and surveillance methods of blood glucose measurement can provide ease of use and simplicity for different individuals while reducing the risks and damages of invasive methods. The non-invasive method based on photoplethysmography (PPG) signal is one of the innovative methods on this topic which numerous studies have been conducted by research centers and various companies. However, due to various reasons, the reviewed dataset was not available and no standard dataset has been published on this topic. The presented dataset, which was sampled by the research team of the digital systems of the University of Science and Technology in Mazandaran, Behshahr, Iran, includes 67 raw PPG signals with 2175 Hz sampling frequency along with labeled data: age, gender, and the invasive blood glucose level which can be used in other studies and learning algorithms.