AI-driven wearable sensors for postoperative monitoring in surgical patients: A systematic review

Artificial intelligence used with wearable technology can be an important modality of treatment in the surgical patient management for recovery and reduction of complications such as hypoxia and infection, bleeding, and organ failure. Traditional monitoring systems, based on periodic measurement of vital signs, often cannot detect subtle physiological changes that herald early clinical deterioration. This systematic review discusses how the integration of artificial intelligence with wearable technology can help address some of the limitations in postoperative monitoring.

We did a Systematic review on literature published between 2000 and 2024 English articles or those with text English translations. A total of 4 full text articles were selected for the examination after reviewing and evaluating the reports for quality and eligibility.

This review has identified those AI-enhanced wearable devices and, in the main, biosensors as well as smartwatches that are mostly good in regard to early diagnosis of complications-hypoxia, arrhythmias, as well as problems concerning hemodynamics. These methodologies showed decreases in the rates of admission, including the staying duration in Intensive Care Units regarding support via using the AI-built Continuous Remote Early Warning Scoring system.

Our Review has elaborated on the role of wearables in neurological and vital parameter monitoring and complication prediction, such as seizures and the comfort and compliance of wearable devices in the early postoperative period for the detection of anomalies in vital signs and demonstrated the utility of AI-reinforced sensors in resource-limited settings.