Detection of the optimal region of interest for camera oximetry

Detection of the optimal region of interest for camera oximetry. Karlen, W., Ansermino, J., M., Dumont, G., A., & Scheffer, C. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society., pages 2263-6, 7, 2013.

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The estimation of heart rate and blood oxygen saturation with an imaging array on a mobile phone (camera oximetry) has great potential for mobile health applications as no additional hardware other than a camera and LED flash enabled phone are required. However, this approach is challenging as the configuration of the camera can negatively influence the estimation quality. Further, the number of photons recorded with the photo detector is largely dependent on the optical path length, resulting in a non-homogeneous image. In this paper we describe a novel method to automatically detect the optimal region of interest (ROI) for the captured image to extract a pulse waveform. We also present a study to select the optimal camera settings, notably the white balance. The experiments show that the incandescent white balance mode is the preferable setting for camera oximetry applications on the tested mobile phone (Samsung Galaxy Ace). Also, the ROI algorithm successfully identifies the frame regions which provide waveforms with the largest amplitudes.

@inproceedings{
 title = {Detection of the optimal region of interest for camera oximetry},
 type = {inproceedings},
 year = {2013},
 keywords = {Consumer health,Emerging IT for efficient/low-cost healthcare deli,Mobile health},
 pages = {2263-6},
 websites = {http://www.ncbi.nlm.nih.gov/pubmed/24110175},
 month = {7},
 city = {Osaka},
 id = {dc31e7c3-2b73-3184-b774-20afacde5063},
 created = {2021-11-19T08:04:09.999Z},
 accessed = {2013-10-23},
 file_attached = {true},
 profile_id = {6d353feb-efe4-367e-84a2-0815eb9ca878},
 last_modified = {2022-09-04T18:12:08.266Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Karlen2013f},
 folder_uuids = {f1f67efc-95a7-4f1a-b181-c3670c667a34,d25bf112-04e3-4db2-9a05-346bfdcbbda2},
 private_publication = {false},
 abstract = {The estimation of heart rate and blood oxygen saturation with an imaging array on a mobile phone (camera oximetry) has great potential for mobile health applications as no additional hardware other than a camera and LED flash enabled phone are required. However, this approach is challenging as the configuration of the camera can negatively influence the estimation quality. Further, the number of photons recorded with the photo detector is largely dependent on the optical path length, resulting in a non-homogeneous image. In this paper we describe a novel method to automatically detect the optimal region of interest (ROI) for the captured image to extract a pulse waveform. We also present a study to select the optimal camera settings, notably the white balance. The experiments show that the incandescent white balance mode is the preferable setting for camera oximetry applications on the tested mobile phone (Samsung Galaxy Ace). Also, the ROI algorithm successfully identifies the frame regions which provide waveforms with the largest amplitudes.},
 bibtype = {inproceedings},
 author = {Karlen, Walter and Ansermino, J Mark and Dumont, Guy A and Scheffer, Cornie},
 doi = {10.1109/EMBC.2013.6609988},
 booktitle = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society.}
}

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