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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

    Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset

    Riaz Muhammad1, Ahmed Ali1, M. Abid Anwar1, Toufique Ahmed Soomro2,*, Omar AlShorman3, Adel Alshahrani4, Mahmoud Masadeh5, Ghulam Md Ashraf6,7, Naif H. Ali8, Muhammad Irfan9, Athanasios Alexiou10

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2821-2835, 2023, DOI:10.32604/iasc.2023.026279

    Abstract Electroencephalogram (EEG) is a method of capturing the electrophysiological signal of the brain. An EEG headset is a wearable device that records electrophysiological data from the brain. This paper presents the design and fabrication of a customized low-cost Electroencephalogram (EEG) headset based on the open-source OpenBCI Ultracortex Mark IV system. The electrode placement locations are modified under a 10–20 standard system. The fabricated headset is then compared to commercially available headsets based on the following parameters: affordability, accessibility, noise, signal quality, and cost. First, the data is recorded from 20 subjects who used the EEG Headset, and signals were recorded.… More >

  • Open Access

    ARTICLE

    Wearable UWB Antenna-Based Bending and Wet Performances for Breast Cancer Detection

    Ali Hanafiah Rambe1, Muzammil Jusoh2,3, Samir Salem Al-Bawri4,5,*, Mahmoud A. Abdelghany6,7

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5575-5587, 2022, DOI:10.32604/cmc.2022.030902

    Abstract This paper proposed integrating the communication system on the garment, which can be utilized to detect breast cancer at an early stage by using an ultra-wideband (UWB) wearable antenna. Breast cancer is an abnormal cell that is located in the breast tissue. Early detection of breast cancer plays an important role, and it helps in the long term for all women. The proposed UWB wearable antenna successfully operates at 3.1–10.6 GHz under an acceptable reflection coefficient of −10 dB. The fabricated wearable antenna was made from Shieldit Super and felt both conductive and nonconductive wearable materials. Few measurement studies of… More >

  • Open Access

    ARTICLE

    Environmental Protection and Energy Color Changing Clothing Design under the Background of Sustainable Development

    Jingyu Dai1,*, Hongyu Dai2, Yutong Xie3, T. Indumathi4

    Journal of Renewable Materials, Vol.10, No.11, pp. 2717-2728, 2022, DOI:10.32604/jrm.2022.019735

    Abstract In order to promote the application of clean energy technology in clothing and promote the integration of industrial development and artificial intelligence wearable technology, this study elaborates the energy application characteristics of intelligent wearable products at home and abroad and its application in different fields, aiming at the current research status of wearable technology in the field of textile and clothing. The wearable distributed generation technology is classified, and a creative clothing design for detecting climate temperature is designed. Based on the monitoring of body temperature, the changes in clothing pattern color can reflect people’s health and emotional status. At… More >

  • Open Access

    ARTICLE

    Silk Fibroin-Based Hydrogel for Multifunctional Wearable Sensors

    Yiming Zhao1,2, Hongsheng Zhao3, Zhili Wei4, Jie Yuan1, Jie Jian1, Fankai Kong1, Haojiang Xie1, Xingliang Xiong1,2,*

    Journal of Renewable Materials, Vol.10, No.11, pp. 2729-2746, 2022, DOI:10.32604/jrm.2022.019721

    Abstract The flexible wearable sensors with excellent stretchability, high sensitivity and good biocompatibility are signifi- cantly required for continuously physical condition tracking in health management and rehabilitation monitoring. Herein, we present a high-performance wearable sensor. The sensor is prepared with nanocomposite hydrogel by using silk fibroin (SF), polyacrylamide (PAM), polydopamine (PDA) and graphene oxide (GO). It can be used to monitor body motions (including large-scale and small-scale motions) as well as human electrophysiological (ECG) signals with high sensitivity, wide sensing range, and fast response time. Therefore, the proposed sensor is promising in the fields of rehabilitation, motion monitoring and disease diagnosis. More >

  • Open Access

    ARTICLE

    Multi-Headed Deep Learning Models to Detect Abnormality of Alzheimer’s Patients

    S. Meenakshi Ammal*, P. S. Manoharan

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 367-390, 2023, DOI:10.32604/csse.2023.025230

    Abstract Worldwide, many elders are suffering from Alzheimer’s disease (AD). The elders with AD exhibit various abnormalities in their activities, such as sleep disturbances, wandering aimlessly, forgetting activities, etc., which are the strong signs and symptoms of AD progression. Recognizing these symptoms in advance could assist to a quicker diagnosis and treatment and to prevent the progression of Disease to the next stage. The proposed method aims to detect the behavioral abnormalities found in Daily activities of AD patients (ADP) using wearables. In the proposed work, a publicly available dataset collected using wearables is applied. Currently, no real-world data is available… More >

  • Open Access

    ARTICLE

    Sport-Related Activity Recognition from Wearable Sensors Using Bidirectional GRU Network

    Sakorn Mekruksavanich1, Anuchit Jitpattanakul2,*

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1907-1925, 2022, DOI:10.32604/iasc.2022.027233

    Abstract Numerous learning-based techniques for effective human activity recognition (HAR) have recently been developed. Wearable inertial sensors are critical for HAR studies to characterize sport-related activities. Smart wearables are now ubiquitous and can benefit people of all ages. HAR investigations typically involve sensor-based evaluation. Sport-related activities are unpredictable and have historically been classified as complex, with conventional machine learning (ML) algorithms applied to resolve HAR issues. The efficiency of machine learning techniques in categorizing data is limited by the human-crafted feature extraction procedure. A deep learning model named MBiGRU (multimodal bidirectional gated recurrent unit) neural network was proposed to recognize everyday… More >

  • Open Access

    ARTICLE

    Improving the Ambient Intelligence Living Using Deep Learning Classifier

    Yazeed Yasin Ghadi1, Mouazma Batool2, Munkhjargal Gochoo3, Suliman A. Alsuhibany4, Tamara al Shloul5, Ahmad Jalal2, Jeongmin Park6,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1037-1053, 2022, DOI:10.32604/cmc.2022.027422

    Abstract Over the last decade, there is a surge of attention in establishing ambient assisted living (AAL) solutions to assist individuals live independently. With a social and economic perspective, the demographic shift toward an elderly population has brought new challenges to today’s society. AAL can offer a variety of solutions for increasing people’s quality of life, allowing them to live healthier and more independently for longer. In this paper, we have proposed a novel AAL solution using a hybrid bidirectional long-term and short-term memory networks (BiLSTM) and convolutional neural network (CNN) classifier. We first pre-processed the signal data, then used time-frequency… More >

  • Open Access

    ARTICLE

    Directional Wideband Wearable Antenna with Circular Parasitic Element for Microwave Imaging Applications

    N. A. Koma'rudin1, Z. Zakaria1,*, A. A. Althuwayb2, H. Lago3, H. Alsariera1, H. Nornikman1, A. J. A. Al-Gburi1, P. J. Soh4,5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 983-998, 2022, DOI:10.32604/cmc.2022.024782

    Abstract This work proposes a wideband and unidirectional antenna consisting of dual layer of coplanar waveguide based on the circular parasitic element technique. The design procedure is implemented in three stages: Design A, which operates at 3.94 GHz with a bandwidth of 3.83 GHz and a fractional bandwidth (FBW) of 97.2%; Design B, which operates at 3.98 GHz with a bandwidth of 0.66 GHz (FBW of 56.53%); and Design C as the final antenna. The final Design C is designed to resonate at several frequencies between 2.89 and 7.0 GHz for microwave imaging applications with a bandwidth of 4.11 GHz (79.8%)… More >

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