Contactless blood pressure sensing using facial visible and thermal images

被引：17

作者：

Oiwa K. ^{[1
]}

Bando S. ^{[1
]}

Nozawa A. ^{[1
]}

机构：

[1] Aoyama Gakuin University, 5-10-1 Fuchinobe, Chuo-ku, Sagamihara, Kanagawa

来源：

Artificial Life and Robotics | 2018年 / 23卷 / 03期

关键词：

Blood pressure sensing; Contactless sensing; Facial thermal images; Facial visible images; Individual model;

D O I：

10.1007/s10015-018-0450-1

中图分类号：

学科分类号：

摘要：

Hypertension is one of the leading risk factors for several diseases. Measurement and monitoring of blood pressure anytime and anywhere are important to lower blood pressure and prevent pathogenesis of diseases. Non-contact blood pressure measurement is desired to monitor blood pressure anytime and anywhere. The aim of this study was to develop a non-contact blood pressure sensing system. A previous study reported that amplitude and time differences of facial photoplethysmogram (PPG) components extracted using brightness variation of facial skin color in facial visible images could be useful indices for estimating blood pressure. The maximum error between measured and estimated blood pressure using facial PPG components was 12 mmHg. An additional signal processing algorithm is desired to increase the accuracy for estimating blood pressure using facial PPG components. By contrast, facial skin temperature also reflects changes in the facial blood circulation. High-accuracy estimation of blood pressure could be expected using both facial PPG components and facial skin temperature. In this study, improvement of accuracy for estimating blood pressure using facial PPG components by attempting to apply additional signal processing to facial skin color variation. Furthermore, a correlation analysis between facial skin temperature and measured blood pressure was performed, and individual models for blood pressure estimation were created. © 2018, ISAROB.

引用

页码：387 / 394

页数：7

共 23 条

[1]

Frostegard J., Immunity, atherosclerosis and cardiovascular disease, BMC Med, 11, (2013)

[2]

Kudo C., Shin W.S., Sasaki N., Harai K., Kato K., Seino H., Goke E., Fujino T., Kuribayashi N., Onuki Pearce Y., Taira M., Matsushima R., Minabe M., Takashiba S., Effects of Periodontal Treatment on Carotid Intima-Media Thickness in Patients with Lifestyle-Related Diseases: Japanese Prospective Multicentre Observational Study, Odontology, pp. 1-12, (2018)

[3]

Halme L., Vesalainen R., Kaaja M., Kantola I., Self-monitoring of blood pressure promotes achievement of blood pressure target in primary health care, Am J Hypertens, 18, pp. 1415-1420, (2005)

[4]

Yong P., Geddes L.A., A surrogate arm for evaluating the accuracy of instruments for indirect measurement of blood pressure, Biomed Instrum Technol, 24, pp. 130-135, (1990)

[5]

van Popele N.M., Grobbee D.E., Bots M.L., Asmar R., Topouchian J., Reneman R.S., Hoeks A.P.G., van der Kuip D.A.M., Hofman A., Witteman J.C.M., Association between arterial stiffness and atherosclerosis the rotterdam study, Stroke, 32, pp. 454-460, (2001)

[6]

Poon C.C.Y., Zhang Y.T., Cuff-less and noninvasive measurements of arterial blood pressure by pulse transit time, engineering in medicine and biology society, 2005, IEEE-EMBS 2005. 27Th Annual International Conference of The. IEEE, pp. 5877-5880, (2006)

[7]

Kim H.L., Seo J.B., Chung W.Y., Kim S.H., Zo J.H., Kim M.A., The association between ambulatory blood pressure profile and Brachialankle pulse wave velocity in untreated hypertensive subjects, Blood Press, 24, pp. 139-146, (2015)

[8]

Jonathan E., Leahy M., Investigating a smartphone imaging unit for photoplethysmography, Physiol Meas, 31, (2010)

[9]

Scully C.G., Lee J., Meyer J., Gorbach A.M., Granquist-Fraser D., Mendelson Y., Chon K.H., Physiological parameter monitoring from optical recordings with a mobile phone, IEEE Trans Biomed Eng, 59, pp. 303-306, (2012)

[10]

Chandrasekaran V., Dantu R., Jonnada S., Thiyagaraja S., Subbu K.P., Cuffless differential blood pressure estimation using smart phones, IEEE Trans Biomed Eng, 60, pp. 1080-1089, (2013)

← 1 2 3 →