• Low-Cost Multisensor Integrated System for Online Walking Gait Detection

      Academic Editor: Ruiz, Carlos; email: carlos.ruiz@unavarra.es; Yan, Lingyun; orcid: 0000-0002-9986-2182; email: lingyun.yan@manchester.ac.uk; Wei, Guowu; orcid: 0000-0003-2613-902X; email: g.wei@salford.ac.uk; Hu, Zheqi; email: zheqi.hu@manchester.ac.uk; Xiu, Haohua; email: xiuhh@jlu.edu.cn; Wei, Yuyang; email: yuyang.wei@manchester.ac.uk; Ren, Lei; orcid: 0000-0003-3222-2102; email: lei.ren@manchester.ac.uk (Hindawi, 2021-08-14)
      A three-dimensional motion capture system is a useful tool for analysing gait patterns during walking or exercising, and it is frequently applied in biomechanical studies. However, most of them are expensive. This study designs a low-cost gait detection system with high accuracy and reliability that is an alternative method/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass-produced low-cost sensors/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100 Hz classifies motion data in real-time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule-based calibration filter to classify kinematic data into five distinct gait events: heel-strike, foot-flat, heel-off, toe-off, and initial-swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2 km/h while kinematic data are recorded by a low-cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32 ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.
    • Recognition of Design Fixation via Body Language Using Computer Vision

      Academic Editor: Zhang, Kai; Yang, Zhongliang; email: yzl@dhu.edu.cn; Chen, Yumiao; orcid: 0000-0002-2702-4649; email: 181603042@qq.com; Zhang, Song; email: zhangrime@gmail.com (Hindawi, 2021-08-27)
      The main objective of this study is to recognize design fixation accurately and effectively. First, we conducted an experiment to record the videos of design process and design sketches from 12 designers for 15 minutes. Then, we executed a video analysis of body language in designers, correlating body language to the presence of design fixation, as judged by a panel of six experts. We found that three body language types were significantly correlated to fixation. A two-step hybrid recognition model of design fixation based on body language was proposed. The first-step recognition model of body language using transfer learning based on a pretrained VGG-16 convolutional neural network was constructed. The average recognition rate achieved by the VGG-16 model was 92.03%. Then, the frames of recognized body language were used as input vectors to the second-step fixation classification model based on support vector machine (SVM). The average recognition rate for the fixation state achieved by the SVM model was 79.11%. The impact of the work could be that the fixation can be detected not only by the sketch outcomes but also by monitoring the movements, expressions, and gestures of designers, as it is happening by monitoring the movements, expressions, and gestures of designers.
    • Studying Effects of Calcium Oxide Nanoparticles on Dentinogenesis in Male Wistar Rats

      Academic Editor: Mallineni, Sreekanth Kumar; Al-Maula, Bushra Habeeb; orcid: 0000-0002-2293-4897; email: bushraalmaula@gmail.com; Wally, Zena Jehad; orcid: 0000-0002-0885-0179; email: zinah.alnuaimi@uokufa.edu.iq; Al-Magsoosi, Mohanad Jameel Najm; orcid: 0000-0002-9007-2870; email: muhanned72@yahoo.com; Dosh, Rasha Hatem; orcid: 0000-0002-2318-6608; email: rasha.dosh@uokufa.edu.iq; Mustafa, Ruba M.; orcid: 0000-0002-3425-459X; email: rmmustafa@just.edu.jo; Al-Nasrawi, Suhad Jabbar Hamed; orcid: 0000-0003-3045-7389; email: suhad.alnasrawi@uokufa.edu.iq; Alfutimie, Abdullatif; orcid: 0000-0002-2531-3762; email: abdullatif.alfutimie@manchester.ac.uk; Haider, Julfikar; orcid: 0000-0001-7010-8285; email: j.haider@mmu.ac.uk (Hindawi, 2021-07-26)
      This study aimed to evaluate potential impacts of calcium oxide nanoparticles (CaO-NPs) at different dosages on predentin thickness, number of blood vessels, periodontal ligament thickness, and blood glucose level of Wistar rats. Twelve rats were randomly gathered into four groups, untreated (control) and CaO-NP-treated groups at three concentrations (25, 50, and 100 mg/kg of the body weight) over a period of 60 days. Histological investigation was performed on twenty-four lower incisor teeth extracted from all the tested groups under a light microscope, and an automatic Fujifilm was used to measure the blood glucose level. The results showed that regular nanoparticle treatment significantly increased predentin and periodontal ligament thicknesses, a gradual decrease in vascularization in the pulp tissue, and an increase in the blood glucose level as the dosages of nanoparticles administered to the rats increased. Administration of the CaO-NPs at low dosage (25 mg/kg) could be beneficial for the growth and integrity of teeth and dentinal tissues in rats.