In this paper, we present a method for recognizing human activity from linguistic summarizations of temporal fuzzy inference curves representing the states of a three-dimensional object called voxel person. A hierarchy of fuzzy logic is used, where the output from each level is summarized and fed into the next level. We present a two level model for fall detection. The first level infers the states of the person at each image. The second level operates on linguistic summarizations of voxel person's states and inference regarding activity is performed. The rules used for fall detection were designed under the supervision of nurses to ensure that they reflect the manner in which elders perform these activities. The proposed framework is extremely flexible. Rules can be modified, added, or removed, allowing for per-resident customization based on knowledge about their cognitive and physical ability.
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http://dx.doi.org/10.1016/j.cviu.2008.07.006 | DOI Listing |
Viruses
January 2025
Département de Virologie, Institut Pasteur de Dakar, Dakar BP 220, Senegal.
Despite extensive experience with influenza surveillance in humans in Senegal, there is limited knowledge about the actual situation and genetic diversity of avian influenza viruses (AIVs) circulating in the country, hindering control measures and pandemic risk assessment. Therefore, as part of the "One Health" approach to influenza surveillance, we conducted active AIV surveillance in two live bird markets (LBMs) in Dakar to better understand the dynamics and diversity of influenza viruses in Senegal, obtain genetic profiles of circulating AIVs, and assess the risk of emergence of novel strains and their transmission to humans. Cloacal swabs from poultry and environmental samples collected weekly from the two LBMs were screened by RT-qPCR for H5, H7, and H9 AIVs.
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January 2025
Department of Mechanical Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal.
Smart textiles provide a significant technological advancement, but their development must balance traditional textile properties with electronic features. To address this challenge, this study introduces a flexible, electrically conductive composite material that can be fabricated using a continuous bi-component extrusion process, making it ideal for sensor electrodes. The primary aim was to create a composite for the filament's core, combining multi-walled carbon nanotubes (MWCNTs), polypropylene (PP), and thermoplastic elastomer (TPE), optimised for conductivity and flexibility.
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January 2025
Faculty of Science and Engineering, Saga University, Saga 840-8502, Japan.
Infrared array sensor-based fall detection and activity recognition systems have gained momentum as promising solutions for enhancing healthcare monitoring and safety in various environments. Unlike camera-based systems, which can be privacy-intrusive, IR array sensors offer a non-invasive, reliable approach for fall detection and activity recognition while preserving privacy. This work proposes a novel method to distinguish between normal motion and fall incidents by analyzing thermal patterns captured by infrared array sensors.
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January 2025
Physiological Controls Research Center, University Research and Innovation Center, Obuda University, 1034 Budapest, Hungary.
In light of the demographic shift towards an aging population, there is an increasing prevalence of dementia among the elderly. The negative impact on mental health is preventing individuals from taking proper care of themselves. For individuals requiring hospital care, those receiving home care, or as a precaution for a specific individual, it is advantageous to utilize monitoring equipment to track their biological parameters on an ongoing basis.
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January 2025
Advanced Institute of Convergence Technology, 145 Gwanggyo-ro, Yeongtong-gu, Suwon-si 16229, Gyeonggi-do, Republic of Korea.
According to South Korea's Ministry of Employment and Labor, approximately 25,000 construction workers suffered from various injuries between 2015 and 2019. Additionally, about 500 fatalities occur annually, and multiple studies are being conducted to prevent these accidents and quickly identify their occurrence to secure the golden time for the injured. Recently, AI-based video analysis systems for detecting safety accidents have been introduced.
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