Browsing by Author "Lin, Kuan-Yi"

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A Robust Vision-Based Heart Rate Evaluation
(2015-01-01)
Lin, Kuan-Yi
;
Chen, Duan-Yu
;
Lee, Suh-Yin
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資訊工程學系
;
Department of Computer Science
Monitoring heart rates using conventional electrocardiogram (ECG) equipment requires patients to wear adhesive gel patches or chest straps that can cause skin irritation and discomfort. Commercially-available pulse oximetry sensors that attach to the fingertips or earlobes also cause inconvenience for patients and the spring-loaded clips can be painful to use. Therefore, a novel robust face-based heart rate monitoring technique is proposed to allow for the evaluation of heart rate variation without physical contact with the patient. Face reflectance is first decomposed from a single image and then heart rate evaluation is conducted from consecutive frames according to the periodic variation of reflectance strength resulting from changes to hemoglobin absorptivity across the visible light spectrum as heartbeats cause changes to blood volume in the blood vessels in the face. To achieve a robust evaluation, ensemble empirical mode decomposition (EEMD) of the Hilbert-Huang Transform (HHT) is used to acquire the primary heart rate signal while reducing the effect of ambient light changes. Our proposed approach is found to outperform the current stateo-f-the-art, providing greater measurement accuracy with smaller variance and is shown to be feasible in real-world environments.
Automatic Human Target Detection and Remote Respiratory Rate Monitoring
(2016)
Lin, Kuan-Yi
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Chen, Duan-Yu
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Yang, Chen
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Chen, Kuo-Jui
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Tsai, Wen-Jiin
Contact measurements of the respiratory rate by using whether conventional electrocardiogram (ECG) equipment or gas sensors with chest straps would cause inconvenience for patients. Therefore, a novel image-based non-contact technique is developed for respiratory rate evaluation and human target detection based on image depth information is also proposed to achieve automatic human target searching and respiration monitoring.
Face-Based Heart Rate Signal Decomposition and Evaluation Using Multiple Linear Regression
(2016-03-01)
Lin, Kuan-Yi
;
Chen, Duan-Yu
;
Tsai, Wen-Jiin
;
資訊工程學系
;
Department of Computer Science
Contact measurements of the cardiac pulse using the conventional electrocardiogram equipment requires patients to wear adhesive gel patches or chest straps that can cause skin irritation and discomfort. Commercially available pulse oximetry sensors that attach to the fingertips or earlobes also cause inconvenience for patients and the spring-loaded clips can be painful to use. Therefore, a novel robust non-contact technique is developed for the evaluation of heart rate variation. According to the periodic variation of reflectance strength resulting from changes to hemoglobin absorptivity across the visible light spectrum as heartbeats cause changes to blood volume in the blood vessels in the face, a reflectance signal is decomposed from consecutive frames of the green channel of the facial region. Furthermore, ensemble empirical mode decomposition of the Hilbert-Huang transform (HHT) is used to acquire the primary heart rate signal while reducing the effect of ambient light changes. The effective instantaneous frequencies from intrinsic mode functions decomposed by HHT are implemented by the multiple-linear regression model to evaluate heart rates before the frequencies were rectified by maximum likelihood method assuming Poisson distribution, and the minimum elapse time for heart rate evaluation is also evaluated in the estimate process. Experimental results show that our proposed approach provides a convenient non-contact method to evaluate heart rate and outperforms the current state-of-the-art method with higher accuracy and smaller variance.
Image Sensor-Based Heart Rate Evaluation From Face Reflectance Using Hilbert-Huang Transform
(2015-01-01)
Chen, Duan-Yu
;
Wang, Jun-Jhe
;
Lin, Kuan-Yi
;
Chang, Hen-Hong
;
Wu, Han-Kuei
Monitoring heart rates using conventional electrocardiogram equipment requires patients to wear adhesive gel patches or chest straps that can cause skin irritation and discomfort. Commercially available pulse oximetry sensors that attach to the fingertips or earlobes also cause inconvenience for patients and the spring-loaded clips can be painful to use. Therefore, a novel robust face-based heart rate monitoring technique is proposed to allow for the evaluation of heart rate variation without physical contact with the patient. Face reflectance is first decomposed from a single image and then heart rate evaluation is conducted from consecutive frames according to the periodic variation of reflectance strength resulting from changes to hemoglobin absorptivity across the visible light spectrum as heartbeats cause changes to blood volume in the blood vessels in the face. To achieve a robust evaluation, ensemble empirical mode decomposition of the Hilbert-Huang transform is used to acquire the primary heart rate signal while reducing the effect of ambient light changes. Our proposed approach is found to outperform the current state of the art, providing greater measurement accuracy with smaller variance and is shown to be feasible in real-world environments.
Image-based Heart Rate Me(1)asurement based on Multiple Regression
(2015)
Lin, Kuan-Yi
;
Chen, Duan-Yu
;
Tsai, Wen-Jiin
;
交大名義發表
;
National Chiao Tung University
Contact measurements of the cardiac pulse by using whether conventional electrocardiogram equipment or commercially-available pulse oximetry sensors would cause inconvenience for patients. Therefore, a novel robust non-contact technique is developed for the evaluation of heart rate variation. Image-based heart rate measurement based on multiple regression method is proposed.
Image-Based Motion-Tolerant Remote Respiratory Rate Evaluation
(2016-05-01)
Lin, Kuan-Yi
;
Chen, Duan-Yu
;
Tsai, Wen-Jiin
;
資訊工程學系
;
Department of Computer Science
Contact measurements of the respiratory rate using conventional electrocardiogram equipment requires patients to wear chest straps that can cause skin irritation and discomfort. Therefore, a real-time robust non-contact technique is developed for the measurement of respiratory rate variation. The changes of a simple harmonic motion between inhalation and exhalation from the human\'s upper body can be observed from visual appearance. Therefore, in this paper, to characterize the motion, a salient region is automatically selected in the energy map resulted from Haar-like features through consecutive frames. Furthermore, a median optical flow signal is used to acquire the primary respiratory rate signal. The effective respiratory frequencies resulted from vertical motion variation are decomposed by median motion signal and then characterized by zero-crossing method before the frequencies were rectified by an estimation using the noise elimination methods. In the experiment, the performance is evaluated using an extensive data set obtained under distinct four respiratory types, regular respiration, respiration with body motion, respiration with distinct poses, and respiration with distinct capturing distances. Our approach develops a convenient non-contact method to evaluate the respiratory rate with the achievement of measurement under farther distance and also outperforms the current state-of-the-art approach in terms of high correlation coefficient. Therefore, the experiment results show its efficacy for real-world environment.