Comparison of Automated Activity Recognition to Provider Observations of Patient Mobility in the ICU
| Autor: | Austin Reiter, Nishi Rawat, Vishal N. Rao, Suchi Saria, Haider Ali, Michael Peven, Christine Shrock |
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| Rok vydání: | 2019 |
| Předmět: |
Male
medicine.medical_specialty medicine.medical_treatment Psychological intervention MEDLINE Critical Care and Intensive Care Medicine law.invention Activity recognition law Medicine Humans Prospective Studies CLIPS Prospective cohort study Early Ambulation computer.programming_language Aged Aged 80 and over Academic Medical Centers Rehabilitation business.industry Intensive care unit Intensive Care Units Emergency medicine Remote Sensing Technology Observational study Female business computer Algorithms |
| Zdroj: | Critical care medicine. 47(9) |
| ISSN: | 1530-0293 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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