Clinical Activity Monitoring System (CATS): an automatic system to quantify bedside clinical activities in the intensive care unit

Peng Guo, Yeong Shiong Chiew, Geoffrey M. Shaw, Lei Shao, Richard Green, Adrian Clark, J. Geoffrey Chase

Research output: Contribution to journalReview ArticleResearchpeer-review

8 Citations (Scopus)

Abstract

Monitoring clinical activity at the bedside in the intensive care unit (ICU) can provide useful information to evaluate nursing care and patient recovery. However, it is labour intensive to quantify these activities and there is a need for an automated method to record and quantify these activities. This paper presents an automated system, Clinical Activity Tracking System (CATS), to monitor and evaluate clinical activity at the patient's bedside. The CATS uses four Microsoft Kinect infrared sensors to track bedside nursing interventions. The system was tested in a simulated environment where test candidates performed different motion paths in the detection area. Two metrics, ‘Distance’ and ‘Dwell time’, were developed to evaluate interventions or workload in the detection area. Results showed that the system can accurately track the intervention performed by individual or multiple subjects. The results of a 30-day, 24-hour preliminary study in an ICU bed space matched clinical expectations. It was found that the average 24-hour intervention is 22.0 minutes/hour. The average intervention during the day time (7 am–11 pm) is 23.6 minutes/hour, 1.4 times higher than 11 pm–7 am, 16.8 minutes/hour. This system provides a unique approach to automatically collect and evaluate nursing interventions that can be used to evaluate patient acuity and workload demand.

Original languageEnglish
Pages (from-to)52-61
Number of pages10
JournalIntensive and Critical Care Nursing
Volume37
DOIs
Publication statusPublished - Dec 2016

Keywords

  • ICU
  • Motion tracking
  • Nurse-to-patient ratio
  • Nursing intervention

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