This paper presents a new dataset for contact-free heart rate estimation in the near-infrared spectrum. Most published works are either using an approach based on RGB cameras or near-infrared light of a specific wavelength. The data from these experiments is usually not available for other researchers so that no public dataset for multi-spectral heart rate estimation exists. Our new contributed dataset consists of 38 subjects, covering a spectral range of 675nm up to 950nm in 25 narrow spectral bands and allows a thorough comparison of heart rate estimation algorithms and the assessment of the chosen wavelength on the measurement accuracy.
Rapczynski, M., Zhang, C., Al-Hamadi, A., & Notni, G. (2018). A multi-spectral database for NIR Heart Rate Estimation. 2018 25th IEEE International Conference on Image Processing (ICIP). https://doi.org/10.1109/icip.2018.8451104