TY - GEN
T1 - CameraHRV
T2 - Optical Diagnostics and Sensing XVIII: Toward Point-of-Care Diagnostics 2018
AU - Pai, Amruta
AU - Veeraraghavan, Ashok
AU - Sabharwal, Ashutosh
N1 - Funding Information:
This work was partially supported by NSF ERC Grant EEC-1648451 (for PATHS-UP ERC). We would also like to thank Mr. Mayank Kumar for his valuable suggestions, and discussions.
Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2018
Y1 - 2018
N2 - The inter-beat-interval (time period of the cardiac cycle) changes slightly for every heartbeat; this variation is measured as Heart Rate Variability (HRV). HRV is presumed to occur due to interactions between the parasym-pathetic and sympathetic nervous system. Therefore, it is sometimes used as an indicator of the stress level of an individual. HRV also reveals some clinical information about cardiac health. Currently, HRV is accurately measured using contact devices such as a pulse oximeter. However, recent research in the field of non-contact imaging Photoplethysmography (iPPG) has made vital sign measurements using just the video recording of any exposed skin (such as a person's face) possible. The current signal processing methods for extracting HRV using peak detection perform well for contact-based systems but have poor performance for the iPPG signals. The main reason for this poor performance is the fact that current methods are sensitive to large noise sources which are often present in iPPG data. Further, current methods are not robust to motion artifacts that are common in iPPG systems. We developed a new algorithm, CameraHRV, for robustly extracting HRV even in low SNR such as is common with iPPG recordings. CameraHRV combined spatial combination and frequency demodulation to obtain HRV from the instantaneous frequency of the iPPG signal. CameraHRV outperforms other current methods of HRV estimation. Ground truth data was obtained from FDA-Approved pulse oximeter for validation purposes. CameraHRV on iPPG data showed an error of 6 milliseconds for low motion and varying skin tone scenarios. The improvement in error was 14%. In case of high motion scenarios like reading, watching and talking, the error was 10 milliseconds.
AB - The inter-beat-interval (time period of the cardiac cycle) changes slightly for every heartbeat; this variation is measured as Heart Rate Variability (HRV). HRV is presumed to occur due to interactions between the parasym-pathetic and sympathetic nervous system. Therefore, it is sometimes used as an indicator of the stress level of an individual. HRV also reveals some clinical information about cardiac health. Currently, HRV is accurately measured using contact devices such as a pulse oximeter. However, recent research in the field of non-contact imaging Photoplethysmography (iPPG) has made vital sign measurements using just the video recording of any exposed skin (such as a person's face) possible. The current signal processing methods for extracting HRV using peak detection perform well for contact-based systems but have poor performance for the iPPG signals. The main reason for this poor performance is the fact that current methods are sensitive to large noise sources which are often present in iPPG data. Further, current methods are not robust to motion artifacts that are common in iPPG systems. We developed a new algorithm, CameraHRV, for robustly extracting HRV even in low SNR such as is common with iPPG recordings. CameraHRV combined spatial combination and frequency demodulation to obtain HRV from the instantaneous frequency of the iPPG signal. CameraHRV outperforms other current methods of HRV estimation. Ground truth data was obtained from FDA-Approved pulse oximeter for validation purposes. CameraHRV on iPPG data showed an error of 6 milliseconds for low motion and varying skin tone scenarios. The improvement in error was 14%. In case of high motion scenarios like reading, watching and talking, the error was 10 milliseconds.
KW - Frequency demodulation
KW - Heart rate variability
KW - Imaging photoplethysmography
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UR - http://www.scopus.com/inward/citedby.url?scp=85045200594&partnerID=8YFLogxK
U2 - 10.1117/12.2289205
DO - 10.1117/12.2289205
M3 - Conference contribution
AN - SCOPUS:85045200594
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Optical Diagnostics and Sensing XVIII
A2 - Cote, Gerard L.
PB - SPIE
Y2 - 29 January 2018 through 30 January 2018
ER -