{"title":"基于面部视频的非接触式血压和心率估计","authors":"Monika Jain, Sujay Deb, A. Subramanyam","doi":"10.1109/MMSP.2016.7813389","DOIUrl":null,"url":null,"abstract":"Hypertension (high blood pressure) is the leading cause for increasing number of premature deaths due to cardiovascular diseases. Continuous hypertension screening seems to be a promising approach in order to take appropriate steps to alleviate hypertension-related diseases. Many studies have shown that physiological signal like Photoplethysmogram (PPG) can be reliably used for predicting the Blood Pressure (BP) and Heart Rate (HR). However, the existing approaches use a transmission or reflective type wearable sensor to collect the PPG signal. These sensors are bulky and mostly require an assistance of a trained medical practitioner; which preclude these approaches from continuous BP monitoring outside the medical centers. In this paper, we propose a novel touchless approach that predicts BP and HR using the face video based PPG. Since the facial video can easily be captured using a consumer grade camera, this approach is a convenient way for continuous hypertension monitoring outside the medical centers. The approach is validated using the face video data collected in our lab, with the ground truth BP and HR measured using a clinically approved BP monitor OMRON HBP1300. Accuracy of the method is measured in terms of normalized mean square error, mean absolute error and error standard deviation; which complies with the standards mentioned by Association for the Advancement of Medical Instrumentation. Two-tailed dependent sample t-test is also conducted to verify that there is no statistically significant difference between the BP and HR predicted using the proposed approach and the BP and HR measured using OMRON.","PeriodicalId":113192,"journal":{"name":"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":"{\"title\":\"Face video based touchless blood pressure and heart rate estimation\",\"authors\":\"Monika Jain, Sujay Deb, A. Subramanyam\",\"doi\":\"10.1109/MMSP.2016.7813389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hypertension (high blood pressure) is the leading cause for increasing number of premature deaths due to cardiovascular diseases. Continuous hypertension screening seems to be a promising approach in order to take appropriate steps to alleviate hypertension-related diseases. Many studies have shown that physiological signal like Photoplethysmogram (PPG) can be reliably used for predicting the Blood Pressure (BP) and Heart Rate (HR). However, the existing approaches use a transmission or reflective type wearable sensor to collect the PPG signal. These sensors are bulky and mostly require an assistance of a trained medical practitioner; which preclude these approaches from continuous BP monitoring outside the medical centers. In this paper, we propose a novel touchless approach that predicts BP and HR using the face video based PPG. Since the facial video can easily be captured using a consumer grade camera, this approach is a convenient way for continuous hypertension monitoring outside the medical centers. The approach is validated using the face video data collected in our lab, with the ground truth BP and HR measured using a clinically approved BP monitor OMRON HBP1300. Accuracy of the method is measured in terms of normalized mean square error, mean absolute error and error standard deviation; which complies with the standards mentioned by Association for the Advancement of Medical Instrumentation. Two-tailed dependent sample t-test is also conducted to verify that there is no statistically significant difference between the BP and HR predicted using the proposed approach and the BP and HR measured using OMRON.\",\"PeriodicalId\":113192,\"journal\":{\"name\":\"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"43\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMSP.2016.7813389\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2016.7813389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Face video based touchless blood pressure and heart rate estimation
Hypertension (high blood pressure) is the leading cause for increasing number of premature deaths due to cardiovascular diseases. Continuous hypertension screening seems to be a promising approach in order to take appropriate steps to alleviate hypertension-related diseases. Many studies have shown that physiological signal like Photoplethysmogram (PPG) can be reliably used for predicting the Blood Pressure (BP) and Heart Rate (HR). However, the existing approaches use a transmission or reflective type wearable sensor to collect the PPG signal. These sensors are bulky and mostly require an assistance of a trained medical practitioner; which preclude these approaches from continuous BP monitoring outside the medical centers. In this paper, we propose a novel touchless approach that predicts BP and HR using the face video based PPG. Since the facial video can easily be captured using a consumer grade camera, this approach is a convenient way for continuous hypertension monitoring outside the medical centers. The approach is validated using the face video data collected in our lab, with the ground truth BP and HR measured using a clinically approved BP monitor OMRON HBP1300. Accuracy of the method is measured in terms of normalized mean square error, mean absolute error and error standard deviation; which complies with the standards mentioned by Association for the Advancement of Medical Instrumentation. Two-tailed dependent sample t-test is also conducted to verify that there is no statistically significant difference between the BP and HR predicted using the proposed approach and the BP and HR measured using OMRON.