Abstract
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.
Original language | English (US) |
---|---|
Pages (from-to) | 1232-1234 |
Number of pages | 3 |
Journal | Critical care medicine |
Volume | 47 |
Issue number | 9 |
DOIs | |
State | Published - 2019 |
Keywords
- Artificial intelligence
- Computer vision
- Intensive care unit
- Mobility
- Rehabilitation
ASJC Scopus subject areas
- Critical Care and Intensive Care Medicine