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

Iwashita, Yuki; Nagumo, Kent; Oiwa, Kosuke; Nozawa, Akio

doi:10.1007/s10015-021-00705-y

Cited by 12 publications

(5 citation statements)

References 22 publications

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“…In particular, the temperature of the facial skin shows a capacitive variation that reflects the dermal-vascular capacity and the heat capacity of the cutaneous tissue. This capacitive variation is spatially dependent on differences in the arrangement of blood vessels and the structure of the cutaneous tissue in the facial skin [ 23 ]. Various articles have evaluated thermographic quantitative changes in facial skin vasomotor neurovegetative activity, that is, they calculated the absolute temperature of the ROI and conjugated gradients [ 19 , 24 ].…”

Section: Discussionmentioning

confidence: 99%

The Use of Thermography as an Auxiliary Method for Monitoring Convalescence after Facelift Surgery: A Case Study

Chudecka

Dmytrzak²,

Leźnicka

et al. 2022

IJERPH

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Although IR thermography is widely used in medical diagnostics, there are no reports that describe the use of IR thermography in the evaluation of post-plastic-surgery regeneration processes. The aim of the study was to evaluate the potential of thermography as a method which, among others, allows us to determine the location and extent of the inflammatory process, supporting the clinical evaluation of the patient’s convalescence after a facelift surgery using the SMAS technique. During the study and in order to monitor the convalescence process, the patient had a series of face thermograms performed before surgery and up to the 6th week after it. The healing process after surgery was multidirectional for the contralateral areas of the face, leading to thermal asymmetry lasting up to the 3rd week of convalescence. The lowest Tmean values for ROIs were recorded in week 3 of the study and then they gradually increased, in week 6 after surgery, to the following values: chin = 33.1 ± 0.72 °C; cheek left = 33.0 ± 0.26 °C; cheek right = 33.2 ± 0.51 °C; ZFL = 33.8 ± 0.45 °C; ZFR = 33.6 ± 0.74 °C; ZLL = 32.6 ±0.55 °C; ZLR = 32.3 ± 0.32 °C. The temperatures of these areas were still lower than the baseline values obtained before surgery by 0.5–1.4 °C. The usefulness of thermography in the evaluation of post-operative convalescence in facial plastic surgery procedures shows potential in the context of diagnostic assessment of the dynamics of changes in the healing process.

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Section: Discussionmentioning

confidence: 99%

The Use of Thermography as an Auxiliary Method for Monitoring Convalescence after Facelift Surgery: A Case Study

Chudecka

Dmytrzak²,

Leźnicka

et al. 2022

IJERPH

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“…A major advantage of this approach is its unobtrusiveness. In particular, the temperature of the facial skin has been the subject of several studies because the face is constantly exposed and can be measured remotely using infrared thermography [ 32 , 33 , 34 , 35 ].…”

Section: Related Workmentioning

confidence: 99%

“…For example, [ 35 ] investigated the use of skin temperature to estimate resting blood pressure by separating acute stress variations using a multiple regression analysis. They reported that the trained model could accurately estimate resting blood pressure from facial thermal images with a root mean square error of 9.90 mmHg [ 35 ]. Another study [ 33 ] examined the utility of infrared thermal imaging for stress research.…”

Section: Related Workmentioning

confidence: 99%

Physiological Signals and Affect as Predictors of Advertising Engagement

Strle

Košir

Burnik

2023

Sensors

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This study investigated the use of affect and physiological signals of heart rate, electrodermal activity, pupil dilation, and skin temperature to classify advertising engagement. The ground truth for the affective and behavioral aspects of ad engagement was collected from 53 young adults using the User Engagement Scale. Three gradient-boosting classifiers, LightGBM (LGBM), HistGradientBoostingClassifier (HGBC), and XGBoost (XGB), were used along with signal fusion to evaluate the performance of different signal combinations as predictors of engagement. The classifiers trained on the fusion of skin temperature, valence, and tiredness (features n = 5) performed better than those trained on all signals (features n = 30). The average AUC ROC scores for the fusion set were XGB = 0.68 (0.10), LGBM = 0.69 (0.07), and HGBC = 0.70 (0.11), compared to the lower scores for the set of all signals (XGB = 0.65 (0.11), LGBM = 0.66 (0.11), HGBC = 0.64 (0.10)). The results also show that the signal fusion set based on skin temperature outperforms the fusion sets of the other three signals. The main finding of this study is the role of specific physiological signals and how their fusion aids in more effective modeling of ad engagement while reducing the number of features.

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“…This BP variability needs to be taken into account in estimating resting BP, and a technique for this has not yet been established. A previous study had reported that features associated with resting BP variability were separated by ICA, with features appearing in the nose, cheek, and lip areas [12]. Furthermore, a general model building for resting BP estimation based on ICA had been conducted [13].…”

Section: Introductionmentioning

confidence: 99%

“…A previous study had reported that features associated with resting BP variability were separated by ICA, with features appearing in the nose, cheek, and lip areas [12]. Furthermore, a general model building for resting BP estimation based on ICA had been conducted [13].…”

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

Self Cite

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

Cited by 12 publications

References 22 publications

The Use of Thermography as an Auxiliary Method for Monitoring Convalescence after Facelift Surgery: A Case Study

The Use of Thermography as an Auxiliary Method for Monitoring Convalescence after Facelift Surgery: A Case Study

Physiological Signals and Affect as Predictors of Advertising Engagement

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

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