Titlebook: 7th International Conference on the Development of Biomedical Engineering in Vietnam (BME7); Translational Health Vo Van Toi ,Trung Quoc Le

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Md Obaidullah Ansari,J. Ghose,R. Kumar year approximately 37.3 million elderly worldwide experience a fall event that is severe enough to require medical attention. This research proposes a system for activity assessment and fall detection intended for in-home applications using the Internet of Things (IoT) for real-time detection of fa

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青春期

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Conference proceedings 2020new challenges, and shaping futuredirections for research in biomedical engineering fields includingmedical instrumentation, bioinformatics, biomechanics, medical imaging,drug delivery therapy, regenerative medicine and entrepreneurship inmedical devices..

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https://doi.org/10.1007/978-3-319-40827-9ixed for a certain period, our device provides a new measuring method without the need for contact and quickly displays results with high accuracy compare with other devices. Moreover, our purpose is to use this device for making the timely diagnosis of malaria through the human temperature in households, schools, and hospitals.

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Advances in Computational Intelligence method has an average detection error rate of 2.3% for systolic and 7.3% for diastolic on the eight testing subjects. The average processing time is 83.5?ms for one-minute of data which can be implemented in real-time wearable devices.

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Kenji Takizawa,Tayfun E. Tezduyard and validated on the Brain Tumor Segmentation Challenge 2013 (BRATS 2013) dataset. Our method obtained the high performance score with the metric values Dice?=?0.83 and sensitivity?=?0.85. These results were compared to the similar methods.

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