| dc.contributor.author | McDuff, Daniel Jonathan | |
| dc.contributor.author | Gontarek, Sarah | |
| dc.contributor.author | Picard, Rosalind W. | |
| dc.date.accessioned | 2017-07-11T14:49:16Z | |
| dc.date.available | 2017-07-11T14:49:16Z | |
| dc.date.issued | 2014-07 | |
| dc.identifier.issn | 0018-9294 | |
| dc.identifier.issn | 1558-2531 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/110626 | |
| dc.description.abstract | We present a new method for measuring photoplethysmogram signals remotely using ambient light and a digital camera that allows for accurate recovery of the waveform morphology (from a distance of 3 m). In particular, we show that the peak-to-peak time between the systolic peak and diastolic peak/inflection can be automatically recovered using the second-order derivative of the remotely measured waveform. We compare measurements from the face with those captured using a contact fingertip sensor and show high agreement in peak and interval timings. Furthermore, we show that results can be significantly improved using orange, green, and cyan color channels compared to the tradition red, green, and blue channel combination. The absolute error in interbeat intervals was 26 ms and the absolute error in mean systolic-diastolic peak-to-peak times was 12 ms. The mean systolic-diastolic peak-to-peak times measured using the contact sensor and the camera were highly correlated, ρ = 0.94 (p <; 0.001). The results were obtained with a camera frame-rate of only 30 Hz. This technology has significant potential for advancing healthcare. | en_US |
| dc.description.sponsorship | MIT Media Member consortium | en_US |
| dc.description.sponsorship | Nihon Denki Kabushiki Kaisha (NEC fellowship) | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1109/TBME.2014.2340991 | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
| dc.source | MIT web domain | en_US |
| dc.title | Remote Detection of Photoplethysmographic Systolic and Diastolic Peaks Using a Digital Camera | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | McDuff, Daniel, Sarah Gontarek, and Rosalind W. Picard. “Remote Detection of Photoplethysmographic Systolic and Diastolic Peaks Using a Digital Camera.” IEEE Trans. Biomed. Eng. 61, no. 12 (December 2014): 2948–2954. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Media Laboratory | en_US |
| dc.contributor.department | Program in Media Arts and Sciences (Massachusetts Institute of Technology) | en_US |
| dc.contributor.mitauthor | McDuff, Daniel Jonathan | |
| dc.contributor.mitauthor | Gontarek, Sarah | |
| dc.contributor.mitauthor | Picard, Rosalind W. | |
| dc.relation.journal | IEEE Transactions on Biomedical Engineering | en_US |
| dc.eprint.version | Author's final manuscript | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dspace.orderedauthors | McDuff, Daniel; Gontarek, Sarah; Picard, Rosalind W. | en_US |
| dspace.embargo.terms | N | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0002-5661-0022 | |
| mit.license | OPEN_ACCESS_POLICY | en_US |