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

Nishi Rawat, Vishal Rao, Michael Peven, Christine Shrock, Austin Reiter, Suchi Saria, Haider Ali

Research output: Contribution to journalArticle


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).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 languageEnglish (US)
Pages (from-to)1232-1234
Number of pages3
JournalCritical care medicine
Issue number9
Publication statusPublished - Sep 1 2019


ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine

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