Baraa Wasfi Salim¹, Bzar Khidir Hussan², Zainab Salih Ageed³, Subhi R. M. Zeebaree^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4593-4609, 2023, DOI:10.32604/cmc.2023.037514

Abstract Recently, human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare systems. Even though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs, physical human action recognition (HAR) through body sensors gives useful information about the lifestyle and functionality of an individual. This article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based Behavior Recognition (ITSOML-BR) technique using body sensor data. The presented ITSOML-BR technique collects data from… More >

Narit Hnoohom¹, Sakorn Mekruksavanich², Anuchit Jitpattanakul^3,4,*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3371-3385, 2023, DOI:10.32604/iasc.2023.036551

Abstract Falls are the contributing factor to both fatal and nonfatal injuries in the elderly. Therefore, pre-impact fall detection, which identifies a fall before the body collides with the floor, would be essential. Recently, researchers have turned their attention from post-impact fall detection to pre-impact fall detection. Pre-impact fall detection solutions typically use either a threshold-based or machine learning-based approach, although the threshold value would be difficult to accurately determine in threshold-based methods. Moreover, while additional features could sometimes assist in categorizing falls and non-falls more precisely, the estimated determination of the significant features would be too time-intensive, thus using a… More >

A. S. M. Sharifuzzaman Sagar¹, Taein Kim¹, Soyoung Park¹, Hee Seh Lee², Hyung Seok Kim^1,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1941-1961, 2023, DOI:10.32604/cmc.2023.035360

Abstract Relative positioning is one of the important techniques in collaborative robotics, autonomous vehicles, and virtual/augmented reality (VR/AR) applications. Recently, ultra-wideband (UWB) has been utilized to calculate relative position as it does not require a line of sight compared to a camera to calculate the range between two objects with centimeter-level accuracy. However, the single UWB range measurement cannot provide the relative position and attitude of any device in three dimensions (3D) because of lacking bearing information. In this paper, we have proposed a UWB-IMU fusion-based relative position system to provide accurate relative position and attitude between wearable Internet of Things… More >

Sakorn Mekruksavanich¹, Anuchit Jitpattanakul^2,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2111-2128, 2023, DOI:10.32604/iasc.2023.033542

Abstract The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturing firm are vital for the rapid and accurate diagnosis of work performance, particularly during the training of a new worker. Various techniques for identifying and detecting worker performance in industrial applications are based on computer vision techniques. Despite widespread computer vision-based approaches, it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where camera deployment is problematic. Through the use of wearable inertial sensors, we propose a deep learning method for automatically recognizing the activities of construction workers. The… More >

K. M. Monica, R. Parvathi^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6229-6249, 2023, DOI:10.32604/cmc.2023.032273

Abstract Human Activity Recognition (HAR) has always been a difficult task to tackle. It is mainly used in security surveillance, human-computer interaction, and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things (IoT). Human Activity Recognition data can be recorded with the help of sensors, images, or smartphones. Recognizing daily routine-based human activities such as walking, standing, sitting, etc., could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network (2D CNN) MODEL, Long Short Term Memory (LSTM) Model, Bidirectional long short-term memory (Bi-LSTM) are used… More >

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 5^th 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 >

Chih-Ta Yen^1,*, 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 >

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 >