Bounded kalman filter method for motion-robust, non-contact heart rate estimation

Sakthi Kumar Arul Prakash, Conrad S. Tucker

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


The authors of this work present a real-time measurement of heart rate across different lighting conditions and motion categories. This is an advancement over existing remote photo plethysmography (rPPG) methods that require a static, controlled environment for heart rate detection, making them impractical for real-world scenarios wherein a patient may be in motion, or remotely connected to a healthcare provider through telehealth technologies. The algorithm aims to minimize motion artifacts such as blurring and noise due to head movements (uniform, random) by employing i) a blur identification and denoising algorithm for each frame and ii) a bounded Kalman filter technique for motion estimation and feature tracking. A case study is presented that demonstrates the feasibility of the algorithm in non-contact estimation of the pulse rate of subjects performing everyday head and body movements. The method in this paper outperforms state of the art rPPG methods in heart rate detection, as revealed by the benchmarked results.

Original languageEnglish (US)
Article number#312465
Pages (from-to)873-897
Number of pages25
JournalBiomedical Optics Express
Issue number2
StatePublished - Feb 1 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Atomic and Molecular Physics, and Optics


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