Browsing by Author "Lin, Tzu-Min"

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A Contactless Sport Training Monitor Based on Facial Expression and Remote-PPG
(2017-01-01)
Wu, Bing-Fei
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Lin, Chun-Hsien
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Huang, Po-Wei
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Lin, Tzu-Min
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Chung, Meng-Liang
To successfully increase athletes' or exercisers' fitness and endurance, the factors of physiological signal, emotion, or the level of fatigue should be considered during the training program. Many clinical decision support systems can assist to monitor the exercisers by some wearable devices. And, the questionnaire should also be taken into account to produce a report. Such process is cumbersome, and the results are not objective. Furthermore, one may feel uncomfortable when wearing the devices during the training program. In this research, the Rating of Perceived Exertion (RPE) is expected to be estimated automatically without any wearable devices and questionnaires. A camera based heart rate detection algorithm and a fatigue expression feature extractor are fused to estimate the RPE value. The results show that our heart rate detection algorithm can be competitive to the wearable devices, and the trend of the detected heart rate is correlated to RPE. Moreover, the fatigue feature can help reduce the error of the estimation.
A Motion Robust Remote-PPG Approach to Driver's Health State Monitoring
(2017-01-01)
Wu, Bing-Fei
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Chu, Yun-Wei
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Huang, Po-Wei
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Chung, Meng-Liang
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Lin, Tzu-Min
With the surging significance of personal health care, driver's physiological state is no longer negligible nowadays. Among all the indicators of health state in human, heart rate (HR) is one of the most cardinal indicators. The commonly used HR measurement is contact-type, might result in driver's distraction and discomfort in the vehicle applications. To cope with this problem, remote photoplethysmography (rPPG) is utilized to monitor HR at a distance via a web camera. Nevertheless, the rPPG is not without its flaw. The main concern of the rPPG technique is the potential not-robustness result from the arbitrary motion. Consequently, the contribution of this paper is to conquer the motion noise when the car is driving and the driver's health state is well monitored to enhance the public safety. The proposed algorithm is investigated in not only the indoor environment but as well the outdoor driving, which contains much more unpredictable motion. With k-nearest neighbor (kNN) classifier on chrominance-based features, the mean square error can be reduced from 30.6 to 2.79 bpm, approaching the medical instrument level. The proposed method can be applied to human improving driving safety for Advanced Driver Assistance Systems.
Camera-based Heart Rate Measurement Using Continuous Wavelet Transform
(2017-01-01)
Wu, Bing-Fei
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Huang, Po-Wei
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Tsou, Tsong-Yang
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Lin, Tzu-Min
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Chung, Meng-Liang
Recent years have seen increased attention being given to measure Heart Rate with remote-PPG. Previous work mainly focused on optimal signal extraction from three channels of a webcam. Several robust signal extraction methods using either optic models or frequency analysis have been discussed before. After applied these algorithms, residual noise still emerges occasionally with short time duration and relative high energy. This paper investigates the cause of residual noise and then proposed an algorithm based on continuous wavelet transform (CWT) to reduce the highly dynamic residual noise. With noise reduction and signal reconstruction, the advantages of both CWT and FFT are integrated to cope with the motion/illuminance induced residual noise. The results obtained by this system show improved SNR ratio and Entropy under both motion and stationary conditions.
Image Based Contactless Blood Pressure Assessment using Pulse Transit Time
(2017-01-01)
Huang, Po-Wei
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Lin, Chun-Hao
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Chung, Meng-Liang
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Lin, Tzu-Min
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Wu, Bing-Fei
Recent years have seen increased attention being given to Blood Pressure (BP) monitoring. Among all kinds of measurements, the monitors based on Pulse Transit Time (PTT) have gain plenty of attention due to its continuous and cuffless features. Additionally, several studies proposed a fancy way to estimate photoplethysmography (PPG) signal simply via a regular webcam. Nevertheless, literatures on issues of integrating these two advanced techniques have emerged on a slowly and scattered way. Furthermore, accuracy of BP prediction model based on PTT is often limited due to the lack of data. To address the above-mentioned problems, we proposed an image based BP measurement algorithm using k-nearest neighbor and transfer learning results from MIMICII database to real task. The study also introduces newly defined PTT features which are especially suitable for image based PPG and domain adaptation. Compared with the state-of-the-art algorithm, root mean square error of SBP evaluation has been reduced from 15.08 to 14.02.
Vision-Based Instant Measurement System for Driver Fatigue Monitoring
(2020-01-01)
Tsai, Yin-Cheng
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Lai, Peng-Wen
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Huang, Po-Wei
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Lin, Tzu-Min
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Wu, Bing-Fei
In this paper, a vision-based physiological signal measurement system is proposed to instantly measure driver fatigue. A remote photoplethysmography (rPPG) signal is a type of physiological signal measured by a camera without any contact device, and it also retains the characteristics of the PPG, which is useful to evaluate fatigue. To solve the inconvenience caused by the traditional contact-based physiological fatigue detection system and to improve the accuracy, the system measures both the motional and physiological information by using one image sensor. In a practical application, the environmental noise would affect the measured signal, and therefore, we performed a preprocessing step on the signal to extract a clear signal. The experiment was designed in collaboration with Taipei Medical University, and a questionnaire-based method was used to define fatigue. The questionnaire that could directly react to the feeling of the subject was treated as our ground truth. The evaluated correlation was 0.89 and the root mean square error was 0.65 for ten-fold cross-validation on the dataset. The trend of driver fatigue could be evaluated without a contact device by the proposed system. This advantage ensures the safety of the driver and reliability of the system.