@article{2599,
  author = {Gašper SlapniÇcar, Erik Dovgan, Andrejaana Andova, Mitja Luštrek},
  title = {Reconstructing PPG Signal from Video Recordings},
  journal = {Progress in Signals and Telecommunication Engineering},
  year = {2018},
  volume = {7},
  number = {2},
  doi = {},
  url = {http://www.dline.info/pste/fulltext/v7n2/pstev7n2_2.pdf},
  abstract = {Physiological signals give important insight regarding some one’s health. It would be in the interest of people to monitor such signals without any wearable devices. We used RGB camera recordings of faces to reconstruct the PPG signal, which can be used to monitor many physiological signals such as heart rate, breathing rate, blood pressure, etc. A
deep learning method was developed to enhance existing state-of-the-art methods. This method uses the output of an existing
method as an input into a LSTM neural network, which substantially improves the reconstruction of PPG.},
}