Riaz Muhammad¹, Ahmed Ali¹, M. Abid Anwar¹, Toufique Ahmed Soomro^2,*, Omar AlShorman³, Adel Alshahrani⁴, Mahmoud Masadeh⁵, Ghulam Md Ashraf^6,7, 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 >

Ali Hanafiah Rambe¹, Muzammil Jusoh^2,3, Samir Salem Al-Bawri^4,5,*, Mahmoud A. Abdelghany^6,7

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 >

Jingyu Dai^1,*, 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 >

Yiming Zhao^1,2, Hongsheng Zhao³, Zhili Wei⁴, Jie Yuan¹, Jie Jian¹, Fankai Kong¹, Haojiang Xie¹, Xingliang Xiong^1,2,*

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 >

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 >

Sakorn Mekruksavanich¹, Anuchit Jitpattanakul^2,*

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 >

Yazeed Yasin Ghadi¹, Mouazma Batool², Munkhjargal Gochoo³, Suliman A. Alsuhibany⁴, Tamara al Shloul⁵, Ahmad Jalal², Jeongmin Park^6,*

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 >

N. A. Koma'rudin¹, Z. Zakaria^1,*, A. A. Althuwayb², H. Lago³, H. Alsariera¹, H. Nornikman¹, A. J. A. Al-Gburi¹, P. J. Soh^4,5

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 >

Anita Gehlot¹, Rajesh Singh¹, Sweety Siwach², Shaik Vaseem Akram¹, Khalid Alsubhi³, Aman Singh^4,*, Irene Delgado Noya^4,5, 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 >

Muhammad Anwar¹, Farhan Masud², Rizwan Aslam Butt³, Sevia Mahdaliza Idrus^4,*, Mohammad Nazir Ahmad⁵, Mohd Yazid Bajuri⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4443-4456, 2022, DOI:10.32604/cmc.2022.022826

Abstract Wireless Body Area Sensor Network (WBASN) is an automated system for remote health monitoring of patients. WBASN under umbrella of Internet of Things (IoT) is comprised of small Biomedical Sensor Nodes (BSNs) that can communicate with each other without human involvement. These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs. The BSNs generate critical data as it is related to patient's health. The data traffic can be classified as Sensitive Data (SD) and Non-sensitive Data (ND) packets based on the value of vital signs. These data packets have… More >