Process Monitoring in the Intensive Care Unit: Assessing Patient Mobility Through Activity Analysis with a Non-Invasive Mobility Sensor
| Autor: | Christine Shrock, Suchi Saria, Nishi Rawat, Austin Reiter, Andy J. Ma |
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| Rok vydání: | 2016 |
| Předmět: |
Adult
Movement Video Recording 02 engineering and technology Sensitivity and Specificity Article law.invention Activity recognition 03 medical and health sciences Patient safety 0302 clinical medicine Cohen's kappa law 0202 electrical engineering electronic engineering information engineering Humans Medicine Routine care business.industry Non invasive Reproducibility of Results Actigraphy medicine.disease Intensive care unit Intensive Care Units Patient room 030228 respiratory system 020201 artificial intelligence & image processing Medical emergency business Algorithms |
| Zdroj: | Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 ISBN: 9783319467191 MICCAI (1) |
| DOI: | 10.1007/978-3-319-46720-7_56 |
| Popis: | Throughout a patient’s stay in the Intensive Care Unit (ICU), accurate measurement of patient mobility, as part of routine care, is helpful in understanding the harmful effects of bedrest [1]. However, mobility is typically measured through observation by a trained and dedicated observer, which is extremely limiting. In this work, we present a video-based automated mobility measurement system called NIMS: Non-Invasive Mobility Sensor. Our main contributions are: (1) a novel multi-person tracking methodology designed for complex environments with occlusion and pose variations, and (2) an application of human-activity attributes in a clinical setting. We demonstrate NIMS on data collected from an active patient room in an adult ICU and show a high inter-rater reliability using a weighted Kappa statistic of 0.86 for automatic prediction of the highest level of patient mobility as compared to clinical experts. |
| Databáze: | OpenAIRE |
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