Intelligent bladder monitoring system based on STM32

Bo Zhan; Xiaodong Yang; Jiping Wang; Gang Yuan; Hui Zhao; Yanyan Zheng; Jialong Tang; Zicong Ge; Haipeng Lv; Zhongyi Wu

doi:10.1117/12.2641448

4 August 2022 Intelligent bladder monitoring system based on STM32

Bo Zhan, Xiaodong Yang, Jiping Wang, Gang Yuan, Hui Zhao, Yanyan Zheng, Jialong Tang, Zicong Ge, Haipeng Lv, Zhongyi Wu

Proceedings Volume 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022); 123060J (2022) https://doi.org/10.1117/12.2641448
Event: Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 2022, Changchun, China

Abstract

With the development of microelectronics technology and the improvement of its basic design, intelligent integration technology based on STM32 is extremely important in the research and development of new medical devices. In treating urinary system-related diseases, it is necessary to carry out intelligent dynamic monitoring, safety monitoring, and remote data management of primary physiological characteristic data such as bladder pressure, intra-abdominal pressure, and urinary catheter pressure. However, there is currently no dedicated real-time monitoring equipment in clinical practice. To solve this clinical need, we designed an intelligent bladder monitoring system based on STM32. The lower computer of the system can monitor the bladder physiological information of the patient in real-time and then transmit the detected data to the upper computer through the LoRa (Long Range Radio) so that doctors and nurses can deal with the abnormal situation of the patient in time, to realize the purpose of comprehensive and effective bladder monitoring. The final experimental results show that the system can effectively combine the conditions of individual patients and, at the same time, consider the bladder pressure and the volume of fluid in the bladder to formulate a personalized discharge plan, minimize the impact of the catheter, and benefit the bladder function training of patients and postoperative recovery.

Citation Download Citation

Bo Zhan, Xiaodong Yang, Jiping Wang, Gang Yuan, Hui Zhao, Yanyan Zheng, Jialong Tang, Zicong Ge, Haipeng Lv, and Zhongyi Wu "Intelligent bladder monitoring system based on STM32", Proc. SPIE 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 123060J (4 August 2022); https://doi.org/10.1117/12.2641448

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KEYWORDS

Bladder

Computing systems

Sensors

Intelligence systems

Data processing

LCDs

Wireless communications

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