Motion Detectors as Additional Monitoring Devices in the Intensive Care Unit—A Proof-of-Concept Study

Background: Monitoring the vital signs of delirious patients in an intensive care unit (ICU) is challenging, as they might (un-)intentionally remove devices attached to their bodies. In mock-up scenarios, we systematically assessed whether a motion detector (MD) attached to the bed may help in ident...

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Vydáno v:Applied sciences Ročník 13; číslo 16; s. 9319
Hlavní autoři: Güder, Gülmisal, von Rein, Eva, Flohr, Thomas, Weismann, Dirk, Schmitt, Dominik, Störk, Stefan, Frantz, Stefan, Kratzer, Vincent, Kendi, Christian
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.08.2023
Témata:
Blood pressure
Cellular telephones
Intensive care
Internet of Things
Internet of Things devices
Monitoring systems
motion detector
Motion detectors
noncontact monitoring
Oxygen saturation
Patients
Germany
ISSN:2076-3417, 2076-3417
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Shrnutí:Background: Monitoring the vital signs of delirious patients in an intensive care unit (ICU) is challenging, as they might (un-)intentionally remove devices attached to their bodies. In mock-up scenarios, we systematically assessed whether a motion detector (MD) attached to the bed may help in identifying emergencies. Methods: We recruited 15 employees of the ICU and equipped an ICU bed with an MD (IRON Software GmbH, Grünwald, Germany). Participants were asked to replay 22 mock-up scenes of one-minute duration each: 12 scenes with movements and 10 without movements, of which 5 were emergency scenes (“lying dead-still, with no or very shallow breathing”). Blinded recordings were presented to an evaluation panel consisting of an experienced ICU nurse and a physician, who was asked to assess and rate the presence of motions. Results: Fifteen participants (nine women; 173 ± 7.0 cm; 78 ± 19 kg) joined the study. In total, 286 out of 330 scenes (86.7%) were rated correctly. Ratings were false negative (FN: “no movements detected, but recorded”) in 7 out of 180 motion scenes (3.9%). Ratings were false positive (FP: “movements detected, but not recorded”) in 37 out of 150 scenes (24.7%), more often in men than women (26 out of 60 vs. 11 out of 90, respectively; p < 0.001). Of note, in 16 of these 37 FP-rated scenes, a vibrating mobile phone was identified as a potential confounder. The emergency scenes were correctly rated in 64 of the 75 runs (85.3%); 10 of the 11 FP-rated scenes occurred in male subjects. Conclusions: The MD allowed for identifying motions of test subjects with high sensitivity (96%) and acceptable specificity (75%). Accuracy might increase further if activities are recorded continuously under real-world conditions.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app13169319