Archived Articles
Systematic Review | Open Access
Published on: 13 Jan 2026
Article ID: wjprm.2026.a1301
The Role of Artificial Intelligence–Based Systems in Early Detection of Patient–Ventilator Asynchrony: Implications for Physical Therapy Practice – A Systematic Review
Background: Patient–ventilator asynchrony (PVA) is a common complication in mechanically ventilated patients, leading to increased morbidity, prolonged ventilation, and respiratory muscle fatigue. Early detection is critical. Artificial intelligence (AI) systems, including convolutional neural networks (CNNs) and machine learning algorithms, have been applied to automate detection.
Objective: To systematically review current evidence on AI-based…
DOI: 10.5281/zenodo.18307632 »
Review Article | Open Access
Published on: 10 Jan 2026
Article ID: wjprm.2026.a1007
Artificial Intelligence in Detecting Ventilator Asynchrony: A New Clinical Window for Physical Therapy Intervention: Narrative Review
IntroductionVentilator asynchrony is a frequent yet under-recognized problem in mechanically ventilated patients. Failure to detect asynchrony early may lead to prolonged ventilation, respiratory muscle weakness, and delayed rehabilitation. Recent advances in artificial intelligence have introduced smart camera and waveform-based systems capable of detecting subtle asynchrony patterns in real time Artificial Intelligence and Smart Monitoring Systems.
