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Keywords = defecation warning

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13 pages, 3107 KiB  
Article
Defecation Warning Monitor Based on ScAlN Piezoelectric Ultrasonic Transducer (PMUT)
by Tao Yao, Jianwei Zong, Haoyue Zhang, Zhiyuan Hou and Liang Lou
Micromachines 2025, 16(5), 498; https://doi.org/10.3390/mi16050498 - 24 Apr 2025
Viewed by 2613
Abstract
This study proposes an innovative health management solution to address the defecation care needs of the elderly population. Traditional post-defecation care methods have significant limitations, particularly imposing a considerable psychological burden on patients. By leveraging the rich physiological information contained in bowel sounds, [...] Read more.
This study proposes an innovative health management solution to address the defecation care needs of the elderly population. Traditional post-defecation care methods have significant limitations, particularly imposing a considerable psychological burden on patients. By leveraging the rich physiological information contained in bowel sounds, in this work, we designed and implemented a wearable defecation warning monitor based on scandium aluminum nitride (ScAlN) piezoelectric thin films and piezoelectric micromachined ultrasonic transducers (PMUTs). The proposed device mainly incorporates two core components: a bowel sound signal acquisition module and a real-time signal display graphical user interface (GUI) developed using the MATLAB R2023a platform. The research focuses on the systematic characterization and comparative analysis of the sound pressure sensitivity of three different signal readout structures. Experimental results demonstrate that the differential readout structure exhibits superior sensitivity. By continuously monitoring bowel sounds in healthy subjects both with and without the urge to defecate using the defecation warning monitor and a modified stethoscope, and conducting a comparative analysis of the experimental data, it is verified that the defecation warning monitor has significant advantages in clinical applications and demonstrates promising potential for defecation warning monitoring. Full article
(This article belongs to the Section A:Physics)
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16 pages, 7855 KiB  
Article
Research on a Defecation Pre-Warning Algorithm for the Disabled Elderly Based on a Semi-Supervised Generative Adversarial Network
by Yanbiao Zou, Shenghong Wu, Tie Zhang and Yuanhang Yang
Sensors 2022, 22(17), 6704; https://doi.org/10.3390/s22176704 - 5 Sep 2022
Cited by 4 | Viewed by 2734
Abstract
The elderly population in China is continuously increasing, and the disabled account for a large proportion of the elderly population. An effective solution is urgently needed for incontinence among disabled elderly people. Compared with disposable adult diapers, artificial sphincter implantation and medication for [...] Read more.
The elderly population in China is continuously increasing, and the disabled account for a large proportion of the elderly population. An effective solution is urgently needed for incontinence among disabled elderly people. Compared with disposable adult diapers, artificial sphincter implantation and medication for incontinence, the defecation pre-warning method is more flexible and convenient. However, due to the complex human physiology and individual differences, its development is limited. Based on the aging trend of the population and clinical needs, this paper proposes a bowel sound acquisition system and a defecation pre-warning method and system based on a semi-supervised generative adversarial network. A network model was established to predict defecation using bowel sounds. The experimental results show that the proposed method can effectively classify bowel sounds with or without defecation tendency, and the accuracy reached 94.4%. Full article
(This article belongs to the Special Issue E-health System Based on Sensors and Artificial Intelligence)
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12 pages, 1426 KiB  
Article
Risk Factors and Spatial Clusters of Cryptosporidium Infection among School-Age Children in a Rural Region of Eastern China
by Hao Zheng, Jianfeng He, Li Wang, Rong Zhang, Zhen Ding and Wenbiao Hu
Int. J. Environ. Res. Public Health 2018, 15(5), 924; https://doi.org/10.3390/ijerph15050924 - 6 May 2018
Cited by 8 | Viewed by 4095
Abstract
The epidemiological features of Cryptosporidium infection among school-age children in China still remain unclear. Hereby, a cross-sectional study of 1637 children aged 3–9 years was designed to investigate the risk factors and spatial clusters of Cryptosporidium infection in a rural region of Eastern [...] Read more.
The epidemiological features of Cryptosporidium infection among school-age children in China still remain unclear. Hereby, a cross-sectional study of 1637 children aged 3–9 years was designed to investigate the risk factors and spatial clusters of Cryptosporidium infection in a rural region of Eastern China. Stool specimens collected from participants were examined using the auramine-phenol and modified acid-fast staining. Univariable and multivariable analyses were performed to identify the risk factors of Cryptospordium infection. The spatial clusters were analyzed by a discrete Poisson model using SaTScan software. Our results showed that the overall prevalence of Cryptosporidium infection was 11‰ in the research region. At the age of 3–6 years (odds ratios (OR) = 3.072, 95% confidence intervals (CI): 1.001–9.427), not washing hands before eating and after defecation (OR = 3.003, 95% CI: 1.060–8.511) were recognized as risk factors. Furthermore, a high-risk spatial cluster (relative risk = 4.220, p = 0.025) was identified. These findings call for effective sustainable interventions including family and school-based hygienic education to reduce the prevalence of Cryptosporidium infection. Therefore, an early warning system based spatiotemporal models with risk factors is required to further improve the effectiveness and efficiency of cryptosporidiosis control in the future. Full article
(This article belongs to the Special Issue Environmental Determinants of Infectious Disease Transmission)
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