Smartphone-based SpO2 measurement by exploiting wavelengths separation and chromophore compensation

Nam Bui, Anh Nguyen, Phuc Nguyen, Hoang Truong, Ashwin Ashok, Thang Dinh, Robin Deterding, Tam Vu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Patients with respiratory diseases require frequent and accurate blood oxygen level monitoring. Existing techniques, however, either need a dedicated hardware or fail to predict lowsaturation levels. To fill in this gap,we propose a phone-based oxygen level estimation system, called PhO2, using camera and flashlight functions that are readily available on today's off-the-shelf smartphones. Since the phone's camera and flashlight were not made for this purpose, utilizing them for oxygen level estimation poses many difficulties. We introduce a cost-effective add-on together with a set of algorithms for spatial and spectral optical signal modulation to amplify the optical signal of interest while minimizing noise. A near-field-based pressure detection and feedback mechanism are also proposed to mitigate the negative impacts of user's behavior during the measurement. We also derive a non-linear referencing model with an outlier removal technique that allows PhO2 to accurately estimate the oxygen level from color intensity ratios produced by the smartphone's camera. An evaluation on COTS smartphone with six subjects shows that PhO2 can estimate the oxygen saturation within 3.5% error rate comparing to FDA-approved gold standard pulse oximetry. In addition, our evaluation in hospitals presents high correlation with ground-truth qualified by the 0.83/1.0 Kendall τ coefficient.

Original languageEnglish
Article numberA9
JournalACM Transactions on Sensor Networks
Issue number1
StatePublished - Jan 9 2020


  • Heart rate variability
  • Near-infrared sensing
  • Optical divider
  • Oxygen saturation
  • Peripheral capillary oxygen saturation
  • Phone camera
  • Phone's add-on
  • Skin colour compensation
  • SpO


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