Wearable Sensors to Monitor in ICU Mobility
DOI:
https://doi.org/10.29070/yqq64623Keywords:
ICU mobility, Wearable sensors, Physiotherapy, Accelerometry, Early mobilization, Critical care rehabilitation, Activity monitoringAbstract
Early mobilization in the intensive care unit (ICU) is an integral part of physiotherapy-led rehabilitation, however it remains difficult to objectively and consistently monitor patient mobility given that current practice is limited by intermittent clinical assessment and electronic health record (EHR)-based documentation. Wearable sensors are an objective and scalable approach to mobility assessment in the critically ill. To assess the validity; efficacy and clinical usability of accelerometry based wearable sensors to monitor mobility profiles in ICU patients from a physiotherapy standpoint. A prospective observational study design was used. Triaxial wearable accelerometers were applied on standardized locations on the body of adult ICU patients. Mobility features derived from the sensors such as activity count, transitions of posture and ambulation events were continuously recorded. This information was verified by direct observation, and contrasted with standard EHR documentation of mobility. We computed sensitivities, agreement measures and regression models to quantify the association between mobility levels as covariates in state-outcome pairings. Wearable sensors had high validity for detecting mobility activities important to ICU care, and superior sensitivity compared to EHR documentation. More independently objectively measured mobility was associated with a shorter ICU LOS and a higher discharge functional status. Wear time of the device and completeness of recording were (very) high, indicating feasibility in the general ICU. Wearable sensors delivers a valid, objective and clinically useful measure of mobility in ICU patients. Incorporated into daily physiotherapy practice they may assist in optimizing early mobilization interventions, provide decision-making structure and potential resource allocation to patient care in the critical care setting.
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1. Ma, A. J., Rawat, N., Reiter, A., Shrock, C., Zhan, A., Stone, A., ... & Saria, S. (2017). Measuring patient mobility in the ICU using a novel noninvasive sensor. Critical care medicine, 45(4), 630-636.
2. Kroll, R. R., McKenzie, E. D., Boyd, J. G., Sheth, P., Howes, D., Wood, M., ... & WEARable Information Technology for hospital INpatients (WEARIT-IN) study group. (2017). Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study. Journal of intensive care, 5(1), 64.
3. Jeffs, E., Vollam, S., Young, J. D., Horsington, L., Lynch, B., & Watkinson, P. J. (2016). Wearable monitors for patients following discharge from an intensive care unit: practical lessons learnt from an observational study. Journal of advanced nursing, 72(8), 1851-1862.
4. Fazio, S., Doroy, A., Da Marto, N., Taylor, S., Anderson, N., Young, H. M., & Adams, J. Y. (2020). Quantifying mobility in the ICU: comparison of electronic health record documentation and accelerometer-based sensors to clinician-annotated video. Critical Care Explorations, 2(4), e0091.
5. Järvelä, K., Takala, P., Michard, F., & Vikatmaa, L. (2022). Clinical evaluation of a wearable sensor for mobile monitoring of respiratory rate on hospital wards. Journal of Clinical Monitoring and Computing, 36(1), 81-86.
6. Reiter, A., Ma, A., Rawat, N., Shrock, C., & Saria, S. (2016, October). Process monitoring in the intensive care unit: Assessing patient mobility through activity analysis with a non-invasive mobility sensor. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 482-490). Cham: Springer International Publishing.
7. Davoudi, A., Malhotra, K. R., Shickel, B., Siegel, S., Williams, S., Ruppert, M., ... & Rashidi, P. (2019). Intelligent ICU for autonomous patient monitoring using pervasive sensing and deep learning. Scientific reports, 9(1), 8020.
8. Appelboom, G., Taylor, B. E., Bruce, E., Bassile, C. C., Malakidis, C., Yang, A., ... & Connolly Jr, E. S. (2015). Mobile phone-connected wearable motion sensors to assess postoperative mobilization. JMIR mHealth and uHealth, 3(3), e3785.
9. Ziegler, S., Schmoor, C., Schöler, L. M., Schepputat, S., Takem, E., Grotejohann, B., ... & Feuchtinger, J. (2023). Potential for reducing immobility times of a mobility monitor in-bed sensor system–a stepped-wedge cluster-randomised trial. BMC nursing, 22(1), 478.
10. Coffman, L. (2018). Patient wearable technology in the ICU. Nursing2020 Critical Care, 13(5), 41-42.
11. Daskivich, T. J., Houman, J., Lopez, M., Luu, M., Fleshner, P., Zaghiyan, K., ... & Spiegel, B. (2019). Association of wearable activity monitors with assessment of daily ambulation and length of stay among patients undergoing major surgery. JAMA network open, 2(2), e187673-e187673.
12. Mantas, J. (2020). Wireless monitoring through wearable devices in the ICU: are we close. Import Health Inf Public Health Dur Pandemic, 272(175), 1.
13. Andrade, E., Quinlan, L., Harte, R., Byrne, D., Fallon, E., Kelly, M., ... & ÓLaighin, G. (2021). Augmenting critical care patient monitoring using wearable technology: review of usability and human factors. JMIR Human Factors, 8(2), e16491.
14. Lee, H., Joseph, B., Enriquez, A., & Najafi, B. (2018). Toward using a smartwatch to monitor frailty in a hospital setting: using a single wrist-wearable sensor to assess frailty in bedbound inpatients. Gerontology, 64(4), 389-400.
15. Breteler, M. J., KleinJan, E. J., Dohmen, D. A., Leenen, L. P., van Hillegersberg, R., Ruurda, J. P., ... & Kalkman, C. J. (2020). Vital signs monitoring with wearable sensors in high-risk surgical patients: a clinical validation study. Anesthesiology, 132(3), 424-439.
16. Turmell, M., Cooley, A., Yap, T. L., Alderden, J., Sabol, V. K., Lin, J. R., & Kennerly, S. M. (2022). Improving pressure injury prevention by using wearable sensors to cue critical care patient repositioning. American Journal of Critical Care, 31(4), 295-305.
17. Sena, J., Mostafiz, M. T., Zhang, J., Davidson, A. E., Bandyopadhyay, S., Nerella, S., ... & Rashidi, P. (2024). Wearable sensors in patient acuity assessment in critical care. Frontiers in Neurology, 15, 1386728.
18. Pickham, D., Berte, N., Pihulic, M., Valdez, A., Mayer, B., & Desai, M. (2018). Effect of a wearable patient sensor on care delivery for preventing pressure injuries in acutely ill adults: A pragmatic randomized clinical trial (LS-HAPI study). International journal of nursing studies, 80, 12-19.
19. Downey, C., Randell, R., Brown, J., & Jayne, D. G. (2018). Continuous versus intermittent vital signs monitoring using a wearable, wireless patch in patients admitted to surgical wards: pilot cluster randomized controlled trial. Journal of medical Internet research, 20(12), e10802.
20. Tan, Y. H., Liao, Y., Tan, Z., & Li, K. H. H. (2021). Application of a machine learning algorithms in a wrist-wearable sensor for patient health monitoring during autonomous hospital bed transport. Sensors, 21(17), 5711.
21. Joshi, M., Ashrafian, H., Aufegger, L., Khan, S., Arora, S., Cooke, G., & Darzi, A. (2019). Wearable sensors to improve detection of patient deterioration. Expert review of medical devices, 16(2), 145-154.
22. Michard, F. (2021). Toward smart monitoring with phones, watches, and wearable sensors. Anesthesiology clinics, 39(3), 555-564.
23. Liu, R., Ramli, A. A., Zhang, H., Henricson, E., & Liu, X. (2021, December). An overview of human activity recognition using wearable sensors: Healthcare and artificial intelligence. In International Conference on Internet of Things (pp. 1-14). Cham: Springer International Publishing.
24. Joshi, M., Archer, S., Morbi, A., Arora, S., Kwasnicki, R., Ashrafian, H., ... & Darzi, A. (2021). Short-term wearable sensors for in-hospital medical and surgical patients: mixed methods analysis of patient perspectives. JMIR Perioperative Medicine, 4(1), e18836.






