Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit

Davoudi, Anis; Shickel, Benjamin; Tighe, Patrick J.; Rashidi, Parisa

doi:10.3389/fdgth.2022.773387

Cited by 3 publications

(2 citation statements)

References 109 publications

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“…As many ICU patients may develop severe critical illness neuropathy due to sedation and immobility, monitoring of the activity level is of prognostic importance [26]. The most common techniques utilized for activity monitoring at the ICU have been wearable accelerometers [10] and imaging techniques [8,9,27]. As wearable devices would probably not be tolerated in patients, who intentionally remove their standard monitoring system, imaging salutation appears more attractive.…”

Section: Discussionmentioning

confidence: 99%

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

Güder,

von Rein,

Flohr

et al. 2023

Applied Sciences

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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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Section: Discussionmentioning

confidence: 99%

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

Güder,

von Rein,

Flohr

et al. 2023

Applied Sciences

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“…We trialed an Intelligent ICU with novel environmental and pervasive sensing technology for 51 patients to assess successful (home or rehabilitation) versus unsuccessful (death or hospice) hospital discharge (Shickel et al 2021). We limited this first model to the motion-detecting accelerometer after a review of the literature assessing most important variables for pervasive monitoring in the ICU (Davoudi et al 2022). Equally important, this study also sought to evaluate transfer learning, where we trained a RNN on a traditional ICU cohort and used it is discovered weight and biases for our intelligent ICU.…”

Section: Intelligent Icumentioning

confidence: 99%

Building an automated, machine learning-enabled platform for predicting post-operative complications

Balch

Ruppert²,

Shickel³

et al. 2023

Physiol. Meas.

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In 2019, the University of Florida College of Medicine launched the MySurgeryRisk algorithm to predict eight major post-operative complications using automatically extracted data from the electronic health record. This project was developed in parallel with our Intelligent Critical Care Center and represents a culmination of efforts to build an efficient and accurate model for data processing and predictive analytics. This paper discusses how our model was constructed and improved upon. We highlight the consolidation of the database, processing of fixed and time-series physiologic measurements, development and training of predictive models, and expansion of those models into different aspects of patient assessment and treatment. We end by discussing future directions of the model.

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Pulse oximetry in pediatric care: Balancing advantages and limitations

Al-Beltagi,

Saeed,

Bediwy

et al. 2024

World J Clin Pediatr

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BACKGROUND Pulse oximetry has become a cornerstone technology in healthcare, providing non-invasive monitoring of oxygen saturation levels and pulse rate. Despite its widespread use, the technology has inherent limitations and challenges that must be addressed to ensure accurate and reliable patient care. AIM To comprehensively evaluate the advantages, limitations, and challenges of pulse oximetry in clinical practice, as well as to propose recommendations for optimizing its use. METHODS A systematic literature review was conducted to identify studies related to pulse oximetry and its applications in various clinical settings. Relevant articles were selected based on predefined inclusion and exclusion criteria, and data were synthesized to provide a comprehensive overview of the topic. RESULTS Pulse oximetry offers numerous advantages, including non-invasiveness, real-time feedback, portability, and cost-effectiveness. However, several limitations and challenges were identified, including motion artifacts, poor peripheral perfusion, ambient light interference, and patient-specific factors such as skin pigmentation and hemoglobin variants. Recommendations for optimizing pulse oximetry use include technological advancements, education and training initiatives, quality assurance protocols, and interdisciplinary collaboration. CONCLUSION Pulse oximetry is crucial in modern healthcare, offering invaluable insights into patients’ oxygenation status. Despite its limitations, pulse oximetry remains an indispensable tool for monitoring patients in diverse clinical settings. By implementing the recommendations outlined in this review, healthcare providers can enhance the effectiveness, accessibility, and safety of pulse oximetry monitoring, ultimately improving patient outcomes and quality of care.

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Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit

Cited by 3 publications

References 109 publications

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

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

Building an automated, machine learning-enabled platform for predicting post-operative complications

Pulse oximetry in pediatric care: Balancing advantages and limitations

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