School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China.
Sensors (Basel). 2022 Sep 5;22(17):6704. doi: 10.3390/s22176704.
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%.
中国的老年人口不断增加，其中残疾人口占很大比例。对于残疾老年人的失禁问题，急需有效的解决方案。与一次性成人尿布、人工括约肌植入和失禁药物相比，排便预警方法更加灵活方便。然而，由于人体生理的复杂性和个体差异，其发展受到限制。基于人口老龄化趋势和临床需求，本文提出了一种肠鸣音采集系统和一种基于半监督生成对抗网络的排便预警方法和系统。建立了一个使用肠鸣音预测排便的网络模型。实验结果表明，该方法能够有效地对有或无排便倾向的肠鸣音进行分类，准确率达到 94.4%。
