The OBF Database: A large face video database for remote physiological signal measurement and atrial fibrillation detection

  • Xiaobai Li
  • , Iman Alikhani
  • , Jingang Shi
  • , Tapio Seppanen
  • , Juhani Junttila
  • , Kirsi Majamaa-Voltti
  • , Mikko Tulppo
  • , Guoying Zhao

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

118 Scopus citations

Abstract

Physiological signals, including heart rate (HR), heart rate variability (HRV), and respiratory frequency (RF) are important indicators of our health, which are usually measured in clinical examinations. Traditional physiological signal measurement often involves contact sensors, which may be inconvenient or cause discomfort in long-term monitoring sessions. Recently, there were studies exploring remote HR measurement from facial videos, and several methods have been proposed. However, previous methods cannot be fairly compared, since they mostly used private, self-collected small datasets as there has been no public benchmark database for the evaluation. Besides, we haven't found any study that validates such methods for clinical applications yet, e.g., diagnosing cardiac arrhythmias/disease, which could be one major goal of this technology. In this paper, we introduce the Oulu Bio-Face (OBF) database as a benchmark set to fill in the blank. The OBF database includes large number of facial videos with simultaneously recorded reference physiological signals. The data were recorded both from healthy subjects and from patients with atrial fibrillation (AF), which is the most common sustained and widespread cardiac arrhythmia encountered in clinical practice. Accuracy of HR, HRV and RF measured from OBF videos are provided as the baseline results for future evaluation. We also demonstrated that the video-extracted HRV features can achieve promising performance for AF detection, which has never been studied before. From a wider outlook, the remote technology may lead to convenient self-examination in mobile condition for earlier diagnosis of the arrhythmia.

Original languageEnglish
Title of host publicationProceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages242-249
Number of pages8
ISBN (Electronic)9781538623350
DOIs
StatePublished - 5 Jun 2018
Externally publishedYes
Event13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018 - Xi'an, China
Duration: 15 May 201819 May 2018

Publication series

NameProceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018

Conference

Conference13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
Country/TerritoryChina
CityXi'an
Period15/05/1819/05/18

Keywords

  • Atrial fibrillation
  • Database
  • Facial video
  • Heart rate
  • Heart rate variability

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