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1.
Cogn Emot ; 36(7): 1429-1439, 2022 11.
Article in English | MEDLINE | ID: mdl-36121056

ABSTRACT

ABSTRACTExperiential and behavioural aspects of emotions can be measured readily but developing a contactless measure of emotions' physiological aspects has been a major challenge. We hypothesised that different emotion-evoking films can produce distinctive facial blood flow patterns that can serve as physiological signatures of discrete emotions. To test this hypothesis, we created a new Transdermal Optical Imaging system that uses a conventional video camera to capture facial blood flows in a contactless manner. Using this and deep machine learning, we analysed videos of the faces of people as they viewed film clips that elicited joy, sadness, disgust, fear or a neutral state. We found that each of these elicited a distinct blood flow pattern in the facial epidermis, and that Transdermal Optical Imaging is an effective contactless and inexpensive tool to the reveal physiological correlates of discrete emotions.


Subject(s)
Disgust , Emotions , Humans , Emotions/physiology , Fear/psychology , Sadness , Motion Pictures , Facial Expression
2.
Circ Cardiovasc Imaging ; 12(8): e008857, 2019 08.
Article in English | MEDLINE | ID: mdl-31382766

ABSTRACT

BACKGROUND: Cuff-based blood pressure measurement lacks comfort and convenience. Here, we examined whether blood pressure can be determined in a contactless manner using a novel smartphone-based technology called transdermal optical imaging. This technology processes imperceptible facial blood flow changes from videos captured with a smartphone camera and uses advanced machine learning to determine blood pressure from the captured signal. METHODS: We enrolled 1328 normotensive adults in our study. We used an advanced machine learning algorithm to create computational models that predict reference systolic, diastolic, and pulse pressure from facial blood flow data. We used 70% of our data set to train these models and 15% of our data set to test them. The remaining 15% of the sample was used to validate model performance. RESULTS: We found that our models predicted blood pressure with a measurement bias±SD of 0.39±7.30 mm Hg for systolic pressure, -0.20±6.00 mm Hg for diastolic pressure, and 0.52±6.42 mm Hg for pulse pressure, respectively. CONCLUSIONS: Our results in normotensive adults fall within 5±8 mm Hg of reference measurements. Future work will determine whether these models meet the clinically accepted accuracy threshold of 5±8 mm Hg when tested on a full range of blood pressures according to international accuracy standards.


Subject(s)
Blood Pressure Determination/instrumentation , Blood Pressure Determination/methods , Image Processing, Computer-Assisted/methods , Optical Imaging/methods , Smartphone , Blood Pressure , Humans , Machine Learning , Reproducibility of Results
3.
Sci Rep ; 8(1): 10588, 2018 Jul 12.
Article in English | MEDLINE | ID: mdl-30002447

ABSTRACT

Human cardiovascular activities are important indicators of a variety of physiological and psychological activities in human neuroscience research. The present proof-of-concept study aimed to reveal the spatiotemporal patterns of cardiovascular activities from the dynamic changes in hemoglobin concentrations in the face. We first recorded the dynamics of facial transdermal blood flow using a digital video camera and the Electrocardiography (ECG) signals using an ECG system simultaneously. Then we decomposed the video imaging data extracted from different sub-regions of a face into independent components using group independent component analysis (group ICA). Finally, the ICA components that included cardiovascular activities were identified by correlating their magnitude spectrum to those obtained from the ECG. We found that cardiovascular activities were associated with five independent components reflecting different spatiotemporal dynamics of facial blood flow changes. The strongest strengths of these ICA components were observed in the bilateral forehead, the left chin, and the left cheek, respectively. Our findings suggest that the cardiovascular activities presented different dynamic properties within different facial sub-regions, respectively. More broadly, the present findings point to the potential of the transdermal optical imaging technology as a new neuroscience methodology to study human physiology and psychology, noninvasively and remotely in a contactless manner.


Subject(s)
Face/blood supply , Image Processing, Computer-Assisted , Optical Imaging/methods , Regional Blood Flow/physiology , Adult , Algorithms , Electrocardiography , Face/diagnostic imaging , Female , Healthy Volunteers , Humans , Male , Young Adult
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