Smart agitation monitor systems and methods with artificial intelligence driven clinical assessment and reporting
A wearable sensor system with machine learning algorithms predicts RASS scores in real-time, addressing the limitations of traditional agitation assessment methods by providing continuous, objective monitoring and standardized data for improved patient care and clinical studies.
WO2026090586A1PCT designated stage Publication Date: 2026-04-30PAVINI MARIE
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2025-10-24
- Publication Date
- 2026-04-30
Smart Images
Figure US2025052555_30042026_PF_FP_ABST
Abstract
Disclosed are smart sensor systems and related methods that integrate machine learning (ML) models to analyze actigraphy data and predict the Richmond Agitation-Sedation Scale (RASS) score. Disclosed systems and related methods continuously track physical movements using ML algorithms to identify patterns in this data and correlate them with RASS scores, thereby providing real-time, data-driven insights that enhance clinical assessments and support informed decision-making about patient care and interventions.
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Citation Information
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