VitalLens: Take A Vital Selfie

Philipp V. Rouast
12/11/2023
cs.CVcs.HC

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Abstract

This report introduces VitalLens, an app that estimates vital signs such as heart rate and respiration rate from selfie video in real time. VitalLens uses a computer vision model trained on a diverse dataset of video and physiological sensor data. We benchmark performance on several diverse datasets, including VV-Medium, which consists of 289 unique participants. VitalLens outperforms several existing methods including POS and MTTS-CAN on all datasets while maintaining a fast inference speed. On VV-Medium, VitalLens achieves mean absolute errors of 0.71 bpm for heart rate estimation, and 0.76 bpm for respiratory rate estimation.

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Cite this paper

@article{rouast2023vitallens,
  title  = {VitalLens: Take A Vital Selfie},
  author = {Philipp V. Rouast},
  year   = {2023},
  eprint = {2312.06892},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.06892v3}
}

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