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  • Open Access

    ARTICLE

    Textile UWB 5G Antenna for Human Blood Clot Measurement

    K. Sugapriya*, S. Omkumar

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 803-818, 2023, DOI:10.32604/iasc.2023.032163

    Abstract The antenna plays an essential role in the medical industry. The short-range 5th Generation (5G) communication can be used for seamless transmission, reception, patient monitoring, sensing and measuring various processes at high speeds. A passive Ultra Wide Band (UWB) antenna, used as a sensor in the measurement of Prothrombin Time (PT) i.e., blood clot is being proposed. The investigated micro-strip patch UWB antenna operating in the frequency range of 3.1 to 10.6 GHz consists of a circular patch with a diamond-shaped slot made of jeans substrate material with good sensing properties is accomplished by adjusting the copper thickness of the… More >

  • Open Access

    ARTICLE

    Feature Fusion-Based Deep Learning Network to Recognize Table Tennis Actions

    Chih-Ta Yen1,*, Tz-Yun Chen2, Un-Hung Chen3, Guo-Chang Wang3, Zong-Xian Chen3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 83-99, 2023, DOI:10.32604/cmc.2023.032739

    Abstract A system for classifying four basic table tennis strokes using wearable devices and deep learning networks is proposed in this study. The wearable device consisted of a six-axis sensor, Raspberry Pi 3, and a power bank. Multiple kernel sizes were used in convolutional neural network (CNN) to evaluate their performance for extracting features. Moreover, a multiscale CNN with two kernel sizes was used to perform feature fusion at different scales in a concatenated manner. The CNN achieved recognition of the four table tennis strokes. Experimental data were obtained from 20 research participants who wore sensors on the back of their… More >

  • Open Access

    ARTICLE

    Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices

    Anita Gehlot1, Rajesh Singh1, Sweety Siwach2, Shaik Vaseem Akram1, Khalid Alsubhi3, Aman Singh4,*, Irene Delgado Noya4,5, Sushabhan Choudhury2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 999-1015, 2022, DOI:10.32604/cmc.2022.023861

    Abstract Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise. Moreover, it is widely utilizing for preventing injuries of athletes during a practice session and in few cases, it leads to muscle fatigue. At present, emerging technology like the internet of things (IoT) and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity. In this study, an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram (sEMG) sensor. Normally, the EMG signal is utilized to display muscle activity. Arduino… More >

  • Open Access

    ARTICLE

    An Overview of the Miniaturization and Endurance for Wearable Devices

    Zhoulei Cao1, Qijun Wen1, Xiaoliang Wang1,*, Qing Yang1, Frank Jiang2

    Journal on Internet of Things, Vol.3, No.1, pp. 11-17, 2021, DOI:10.32604/jiot.2021.010404

    Abstract The miniaturization and endurance of wearable devices have been the research direction for a long time. With the development of nanotechnology and the emergence of microelectronics products, people have explored many new strategies that may be applied to wearable devices. In this overview, we will summarize the recent research of wearable devices in these two directions, and summarize some available related technologies. More >

  • Open Access

    ARTICLE

    Reducing Operational Time Complexity of k-NN Algorithms Using Clustering in Wrist-Activity Recognition

    Sun-Taag Choe, We-Duke Cho*, Jai-Hoon Kim, and Ki-Hyung Kim

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 679-691, 2020, DOI:10.32604/iasc.2020.010102

    Abstract Recent research on activity recognition in wearable devices has identified a key challenge: k-nearest neighbors (k-NN) algorithms have a high operational time complexity. Thus, these algorithms are difficult to utilize in embedded wearable devices. Herein, we propose a method for reducing this complexity. We apply a clustering algorithm for learning data and assign labels to each cluster according to the maximum likelihood. Experimental results show that the proposed method achieves effective operational levels for implementation in embedded devices; however, the accuracy is slightly lower than that of a traditional k-NN algorithm. Additionally, our method provides the advantage of controlling the… More >

  • Open Access

    ARTICLE

    Developing a New Security Framework for Bluetooth Low Energy Devices

    Qiaoyang Zhang1, Zhiyao Liang1,*, Zhiping Cai2

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 457-471, 2019, DOI:10.32604/cmc.2019.03758

    Abstract Wearable devices are becoming more popular in our daily life. They are usually used to monitor health status, track fitness data, or even do medical tests, etc. Since the wearable devices can obtain a lot of personal data, their security issues are very important. Motivated by the consideration that the current pairing mechanisms of Bluetooth Low Energy (BLE) are commonly impractical or insecure for many BLE based wearable devices nowadays, we design and implement a security framework in order to protect the communication between these devices. The security framework is a supplement to the Bluetooth pairing mechanisms and is compatible… More >

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