Comparison of Automated Activity Recognition to Provider Observations of Patient Mobility in the ICU.

CRITICAL CARE MEDICINE(2019)

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摘要
Objectives: To compare noninvasive mobility sensor patient motion signature to direct observations by physicians and nurses. Design: Prospective, observational study. Setting: Academic hospital surgical ICU. Patients and Measurements: A total of 2,426 1-minute clips from six ICU patients (development dataset) and 4,824 1-minute clips from five patients (test dataset). Interventions: None. Main Results: Noninvasive mobility sensor achieved a minute-level accuracy of 94.2% (2,138/2,272) and an hour-level accuracy of 81.4% (70/86). Conclusions: The automated noninvasive mobility sensor system represents a significant departure from current manual measurement and reporting used in clinical care, lowering the burden of measurement and documentation on caregivers.
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关键词
artificial intelligence,computer vision,intensive care unit,mobility,rehabilitation
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