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.

血糖检测的无创监测与筛查方法，可为不同人群带来便捷易用、流程简洁的使用体验，同时降低有创检测方式带来的风险与身体损伤。基于光电容积脉搏波（photoplethysmography, PPG）信号的无创检测方案是该领域的创新方向之一，诸多研究中心与企业已围绕此主题开展了大量研究。然而受诸多因素制约，当前经梳理的可用数据集均无法获取，该领域尚未发布标准化的公开数据集。本数据集由伊朗马赞德兰省贝什赫尔市科技大学数字系统研究团队采集构建，包含67条采样频率为2175 Hz的原始PPG信号，以及配套的标注数据：年龄、性别与有创血糖值，可供后续各类研究与学习算法使用。