A Machine Learning Based Intelligent Household Peritoneal Dialysis System

According to the Kidney Disease Annual Report of Taiwan, approximately 12% of the population suffers from kidney disease, making it a significant healthcare issue in the context of an aging population. Peritoneal dialysis is a self-care method for treating kidney disease, which can be manually performed by trained caregivers or patients themselves. However, improper operation may lead to complications such as air embolism or peritonitis. To address this issue, this study proposes an intelligent peritoneal dialysis system that incorporates voice recognition, allowing users to easily initiate the system through verbal commands and automatically complete the fluid exchange process. Particularly, the system integrates machine learning capabilities to provide a comprehensive rating of each dialysis session, enabling users to assess the exchange process and receive corresponding improvement suggestions. This aims to enhance patients' user experience and treatment effectiveness.