Chun-Yueh Yen’s research while affiliated with National Cheng Kung University and other places

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Publications (7)


A Deep Learning-Based Cloud-Edge Healthcare System With Time-of-Flight Cameras
  • Article

March 2024

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34 Reads

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1 Citation

IEEE Sensors Journal

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Ting-Yun Huang

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Chun-Yueh Yen

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[...]

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This study proposes a comprehensive and vision-based long-term healthcare system that includes time-of-flight (ToF) cameras at the front end, the Raspberry Pi at the edge point, and image database and classification at a cloud server. First, the ToF cameras capture human actions through depth maps. Next, the Raspberry Pi accomplishes image preprocessing and sends the resulting images to the cloud server by wireless transmission. Finally, the cloud server performs human action recognition by using the proposed temporal frame correlation recognition model. Our model expands object detection to the three-dimensional space based on continuous ToF images. Depth maps of ToF images do not record users’ identities or environments, which prevents users from committing privacy violations. The study also builds a human action dataset, where each frame is recorded and labeled as five actions including sitting, standing, lying, getting up, and falling. After further optimization in the future, the system can improve the long-term healthcare environment and relieve the burden of nursing on elderly care.


Live Demonstration: An AIoT Wearable ECG Patch with Decision Tree for Arrhythmia Analysis
  • Conference Paper
  • Full-text available

October 2019

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46 Reads

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7 Citations

Download



Fig 1. Association of ECG and Heart Sound
An Intelligent Stethoscope with ECG and Heart Sound Synchronous Display

May 2019

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2,570 Reads

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13 Citations



Citations (7)


... The 2 conv layers CNN in [10] achieves 86.3 mean accuracy on 6 classes with a 32 × 32 ToF. Therefore, ToF classification is performed with relatively complex network models [8], [11]- [13], requiring computing capabilities not suitable for the implementation in a dedicated HW core embedded in the sensing element [14]- [16]. In this work, we demonstrate for the first time in the literature that Ultra-Low resolution (ULR) ToF (8x8 pixels) can be successfully used as a stand-alone sensor for multi-class object classification, even if it is combined with a simple Convolutional Neural Network (CNN), suitable to be processed in the circuitry already equipping the sensor. ...

Reference:

Multiclass Object Classification Using Ultra-Low Resolution Time-of-Flight Sensors
A Deep Learning-Based Cloud-Edge Healthcare System With Time-of-Flight Cameras
  • Citing Article
  • March 2024

IEEE Sensors Journal

... The experiment has been performed to prove the efficiency of the proposed classification algorithm with the standard machine learning classifiers such as Support Vector Machine (SVM) [6], Naive Bayes (NB) [25], and Decision Tree (DT) [12]. All these experiments have been performed by 10-fold cross-validation. ...

Live Demonstration: An AIoT Wearable ECG Patch with Decision Tree for Arrhythmia Analysis

... This study can be compared with some previous studies [29][30][31] that similarly utilized wearable electrocardiographs, data collection for servers, application of noise filters, use of a convolutional neural network, learning with the public MIT-BIH databases, and their integration into an app service. Compared to these studies, this research incorporated methodological improvements. ...

Artificial Intelligence of Things Wearable System for Cardiac Disease Detection

... Phonocardiography, the graphic recording of heart sounds, offers a more analytical approach to cardiac auscultation [4]. Unlike the ephemeral nature of live listening, phonocardiograms provide a tangible, visual representation of cardiac acoustics, allowing for a detailed examination of heart sound waveforms. ...

An Intelligent Stethoscope with ECG and Heart Sound Synchronous Display

... Hz [13]. Can be seen also on High Pass Filter data table that the frequency is below the cutoff has a small output as well as table data Low Pass Filter that the frequency above the cutoff has an output that is small [22][23] [24]. In this study, the researcher used an input of 4.4 volts [25], Cardiac signals that are captured and processed by the device This electric stethoscope is successfully displayed on the PC display and sending signals to the Bluetooth headset and the user can select the signal to be transmitted to the Bluetooth headset [27]. ...

Live Demonstration: An Intelligent Stethoscope with ECG and Heart Sound Synchronous Display

... These integral computing chips facilitate the functionality of a multitude of devices, ranging from everyday gadgets like smart watches 1) to more advanced systems pivotal in emerging applications like Internet of Things (IoT) edge and cloud computing, 2) Augmented Reality, 3) Virtual Reality, 4) autonomous vehicles, 5) and smart healthcare devices. 6) In the heart of the MCUs, there is a type of memory known as read only memory (ROM) mostly using an embedded NOR Flash (eFLASH), 7) which is responsible for storing the instructions that the MCUs need to function. However, with the rise of applications requiring quick responses and efficient energy use, such as IoT edge devices and cloud computing platforms, the eFLASH is hitting a wall due to its relatively high energy consumption and physical scaling limits. ...

Smart Pet Clothing for Monitoring of Health and Mood