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. 2017 Nov 21:5:64.
doi: 10.1186/s40560-017-0261-9. eCollection 2017.

Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study

Ryan R Kroll #  1 , Erica D McKenzie #  2 , J Gordon Boyd  1   3 , Prameet Sheth  4 , Daniel Howes  1   5 , Michael Wood  6 , David M Maslove  1   3   7 ; WEARable Information Technology for hospital INpatients (WEARIT-IN) study group
Affiliations

Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study

Ryan R Kroll et al. J Intensive Care. .

Abstract

Background: Wearable devices generate signals detecting activity, sleep, and heart rate, all of which could enable detailed and near-continuous characterization of recovery following critical illness.

Methods: To determine the feasibility of using a wrist-worn personal fitness tracker among patients recovering from critical illness, we conducted a prospective observational study of a convenience sample of 50 stable ICU patients. We assessed device wearability, the extent of data capture, sensitivity and specificity for detecting heart rate excursions, and correlations with questionnaire-derived sleep quality measures.

Results: Wearable devices were worn over a 24-h period, with excellent capture of data. While specificity for the detection of tachycardia was high (98.8%), sensitivity was low to moderate (69.5%). There was a moderate correlation between wearable-derived sleep duration and questionnaire-derived sleep quality (r = 0.33, P = 0.03). Devices were well-tolerated and demonstrated no degradation in quality of data acquisition over time.

Conclusions: We found that wearable devices could be worn by patients recovering from critical illness and could generate useful data for the majority of patients with little adverse effect. Further development and study are needed to better define and enhance the role of wearables in the monitoring of post-ICU recovery.

Trial registration: Clinicaltrials.gov, NCT02527408.

Keywords: Critical care; Heart rate monitoring; Medical informatics; Mobile health technologies; Sleep quality; Validation study; Wearable devices.

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Conflict of interest statement

Ethics approval and consent to participate

All participating patients, or substitute decision makers on their behalf, provided written informed consent for participation in this study. The Health Sciences Research Ethics Board at Queen’s University reviewed and approved the study protocol, and the trial was registered with clinicaltrials.gov (NCT02527408).

Consent for publication

The patient depicted in Fig. 1 provided consent for the photo to be published in this manuscript.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
The Fitbit Charge HR device used in the study (a). The wearable device as worn by a patient on the inpatient ward following ICU discharge (b)
Fig. 2
Fig. 2
Accuracy of wearable-derived heart rates for the detection of tachycardia (HR > 100) or bradycardia (HR < 50) as determined by SPO2 heart rates. The SPO2-derived values (dark gray) are shown sorted from lowest to highest heart rate. The corresponding wearable-derived heart rate is shown in either light gray (correct classification), green (false positive), or red (false negative). The majority of misclassified heart rates are false negatives for the detection of tachycardia. Some misclassification is due to wearable device readings of “0,” reflecting data not captured by the device
Fig. 3
Fig. 3
Correlation between mean score on the Richards-Campbell Sleep Questionnaire (RCSQ) and wearable-derived measure of the number of minutes asleep overnight (between 22:00 and 06:00). The Pearson correlation coefficient was 0.33 (95% CI 0.04 - 0.58)
See this image and copyright information in PMC

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