PhO2: Smartphone based Blood Oxygen Level Measurement Systems using Near-IR and RED Wave-guided Light

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations

Abstract

Accurately measuring and monitoring patient's blood oxygen level plays a critical role in today’s clinical diagnosis and healthcare practices. Existing techniques however either require a dedicated hardware or produce inaccurate measurements. 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 smart phones. Since phone’s camera and flashlight are not made for this purpose, utilizing them for oxygen level estimation poses many challenges. 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 light-based pressure detection algorithm 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 that allows PhO2 to estimate the oxygen level from color intensity ratios produced by smartphone’s camera. An evaluation using a custom-built optical element on COTS smartphone with 6 subjects shows that PhO2 can estimate the oxygen saturation within 3.5% error rate comparing to FDA-approved gold standard pulse oximetry. A user study to gauge the reception of PhO2 shows that users are comfortable self-operating the device, and willing to carry the device when going out.

Original languageEnglish
Title of host publicationSenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
EditorsRasit Eskicioglu
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450354592
DOIs
StatePublished - Nov 6 2017
Event15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017 - Delft, Netherlands
Duration: Nov 6 2017Nov 8 2017

Publication series

NameSenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
Volume2017-January

Conference

Conference15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017
Country/TerritoryNetherlands
CityDelft
Period11/6/1711/8/17

Funding

We thank the shepherd Neal Patwari and the anonymous ACM SenSys reviewers for their insightful comments. This research is partially supported by the Schramm Foundation, the Colorado Advanced Industries Accelerator (AIA), and U.S. National Science Foundation grant #1602428.

Funder number
1602428

    Keywords

    • Near-infrared sensing
    • Optical divider
    • Oxygen saturation
    • Phone camera
    • Phone’s add-on

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