Intelligent Monitoring System Based on Computer Vision and Artificial Intelligence.
10.12455/j.issn.1671-7104.240287
- Author:
Mingxi ZHANG
1
;
Yirong HONG
1
Author Information
1. The Eye Hospital of Wenzhou Medical University, Wenzhou,
- Publication Type:Journal Article
- Keywords:
artificial intelligence (AI);
computer vision;
intelligent monitoring system
- MeSH:
Artificial Intelligence;
Humans;
Monitoring, Physiologic/methods*;
Algorithms
- From:
Chinese Journal of Medical Instrumentation
2025;49(1):74-79
- CountryChina
- Language:Chinese
-
Abstract:
To ensure the quality of care for inpatients in ophthalmic hospitals, address the complex and variable conditions of postoperative patients, and conduct more comprehensive, accurate and real-time monitoring of patients, an intelligent monitoring system based on computer vision and artificial intelligence has been designed. This system is employed for real-time monitoring of patient health conditions and intelligent care, with primary applications in medical monitoring, rehabilitation therapy, and inpatient care. It comprises intelligent data acquisition devices, smart cameras, continuous physiological data analysis algorithms, AI algorithms, and software. Given the complex and variable conditions of postoperative patients in ophthalmic hospitals, a comprehensive, accurate, and real-time monitoring of patients is required. Therefore, it is necessary to explore a monitoring technology that imposes low physiological and psychological burdens. The intelligent monitoring system can continuously collect patients' physiological parameter indicators and transmit the monitoring data to doctors' workstations or nurse stations after analysis using intelligent algorithms, providing new tools for patient monitoring, disease assessment, risk warning, and more. Furthermore, through the application of computer vision and artificial intelligence technologies, the system can analyze facial expressions, body postures, and other data to identify patients' emotional states and bedridden postures, enabling the timely detection of abnormal situations and implementation corresponding measures. This helps improving the daily work of medical staff, enhance the nursing safety in single-patient rooms in wards, and potentially find applications in the care of critically ill patients and elderly patients, thereby improving nursing efficiency and quality.
