Relationship  between mechanisms of blood pressure change and facial skin temperature distribution

Nakane, Narushi; Oiwa, Kosuke; Nozawa, Akio

doi:10.1007/s10015-019-00565-7

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…We defined 25 regions of interest, indicated by the blue circles in Fig. 1 based on the physiological and psychological significance of the sites [5]. The area of the region was defined as a radius of half the nasal width.…”

Section: Time-series Correlationmentioning

confidence: 99%

Classification of Stress Coping Styles Based on Time Series Correlation of Face Area Temperature

Nakamura

Nagumo

Oiwa

et al. 2022

IEEJ Transactions Elec Engng

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It is hoped that remotely classifying stress‐coping styles can be applied to decisions about how to approach things, learning, etc. In this study, we devised a classification method for stress coping styles based on the time‐series correlation of facial area temperature. As a result, we were able to classify stress coping styles with about 70% probability. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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Section: Time-series Correlationmentioning

confidence: 99%

Classification of Stress Coping Styles Based on Time Series Correlation of Face Area Temperature

Nakamura

Nagumo

Oiwa

et al. 2022

IEEJ Transactions Elec Engng

Self Cite

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“…5, and these regions were suggested to be related to resting blood pressure. In a previous study, the nose region was extracted as feature quantities related to short-term blood pressure variations based on acute stress [26]. The nasal and lip region is well known as the peripheral region reflecting the blood flow variation [27].…”

Section: Construction Of Model For Resting Blood Pressure Estimationmentioning

confidence: 99%

Estimation of resting blood pressure using facial thermal images by separating acute stress variations

Iwashita

Nagumo

Oiwa

et al. 2021

Artif Life Robotics

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The increasing number of people with hypertension worldwide has become a matter of grave concern. Blood pressure monitoring using a non-contact measurement technique is expected to detect and control this medical condition. Previous studies have estimated blood pressure variations following an acute stress response based on facial thermal images obtained from infrared thermography devices. However, a non-contact resting blood pressure estimation method is required because blood pressure is generally measured in the resting state without inducing acute stress. Day-long blood pressure variations include short-term variations due to acute stress and long-term variations in circadian rhythms. The aim of this study is to estimate resting blood pressure from facial thermal images by separating and excluding short-term variations related to acute stress. To achieve this, short-term blood pressure variations components related to acute stress on facial thermal images were separated using independent component analysis. Resting blood pressure was estimated with the extracted independent components excluding the short-term components using multiple regression analysis. The results show that the proposed approach can accurately estimate resting blood pressure from facial thermal images, with a 9.90 mmHg root mean square error. In addition, features related to resting blood pressure were represented in the nose, lip, and cheek regions.

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“…As an initial study of this attempt, a thermo-hue hemodynamic analysis method, which uses spatial features obtained from facial visible and thermal images, had been developed [7]. In previous studies using only FTIs, deep learning algorithms [8] or independent component analysis (ICA) [9] was used to estimate BP, which was artificially induced acute BP variability. However, in general, BP is measured in the resting state.…”

Section: Introductionmentioning

confidence: 99%

An Optimization for Resting Blood Pressure Estimation Model Based on Independent Components of Facial Thermal Images

Ito,

Nagumo,

Oiwa

et al. 2024

IEEJ Transactions Elec Engng

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The increasing number of patients with hypertension is a problem worldwide. Daily blood pressure monitoring is important for the prevention of this disease, and a non‐contact measurement method is desirable. A previous study applied independent components analysis to facial skin temperatures measured remotely using a thermography device for extracting features related to resting blood pressure. Then, a blood pressure estimation model was constructed and obtained an accuracy of 7.73 mmHg root mean square error. However, this previous study did not consider the variables selection methods and models to be constructed. Considering these factors is expected to improve the accuracy of estimation. The objective of this study is to optimize the resting blood pressure estimation model. Two variable selection methods and three modeling methods were applied to independent components of facial thermal images, and the accuracy was compared. The result showed an accuracy of 6.80 mmHg root mean square error with a pattern of support vector regression model using independent components selected by Boruta. In addition, eight explanatory variables were selected by Boruta, and suggesting that the lip, orbital, and lateral nasal regions were related to resting blood pressure. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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Relationship between mechanisms of blood pressure change and facial skin temperature distribution

Cited by 7 publications

References 16 publications

Classification of Stress Coping Styles Based on Time Series Correlation of Face Area Temperature

Classification of Stress Coping Styles Based on Time Series Correlation of Face Area Temperature

Estimation of resting blood pressure using facial thermal images by separating acute stress variations

An Optimization for Resting Blood Pressure Estimation Model Based on Independent Components of Facial Thermal Images

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