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. 2023 May 10;23(10):4632.
doi: 10.3390/s23104632.

Accuracy of a Smartwatch to Assess Heart Rate Monitoring and Atrial Fibrillation in Stroke Patients

Claudia Meza  1   2   3 , Jesus Juega  1   2   3 , Jaume Francisco  2   4 , Alba Santos  2   4 , Laura Duran  4 , Maite Rodriguez  1   2 , Jose Alvarez-Sabin  1 , Laia Sero  5 , Xavier Ustrell  5 , Saima Bashir  6   7 , Joaquín Serena  6   7 , Yolanda Silva  6   7 , Carlos Molina  1   2 , Jorge Pagola  1   2   3
Affiliations

Accuracy of a Smartwatch to Assess Heart Rate Monitoring and Atrial Fibrillation in Stroke Patients

Claudia Meza et al. Sensors (Basel). .

Abstract

(1) Background: Consumer smartwatches may be a helpful tool to screen for atrial fibrillation (AF). However, validation studies on older stroke patients remain scarce. The aim of this pilot study from RCT NCT05565781 was to validate the resting heart rate (HR) measurement and the irregular rhythm notification (IRN) feature in stroke patients in sinus rhythm (SR) and AF. (2) Methods: Resting clinical HR measurements (every 5 min) were assessed using continuous bedside ECG monitoring (CEM) and the Fitbit Charge 5 (FC5). IRNs were gathered after at least 4 h of CEM. Lin's concordance correlation coefficient (CCC), Bland-Altman analysis, and mean absolute percentage error (MAPE) were used for agreement and accuracy assessment. (3) Results: In all, 526 individual pairs of measurements were obtained from 70 stroke patients-age 79.4 years (SD ± 10.2), 63% females, BMI 26.3 (IQ 22.2-30.5), and NIHSS score 8 (IQR 1.5-20). The agreement between the FC5 and CEM was good (CCC 0.791) when evaluating paired HR measurements in SR. Meanwhile, the FC5 provided weak agreement (CCC 0.211) and low accuracy (MAPE 16.48%) when compared to CEM recordings in AF. Regarding the accuracy of the IRN feature, analysis found a low sensitivity (34%) and high specificity (100%) for detecting AF. (4) Conclusion: The FC5 was accurate at assessing the HR during SR, but the accuracy during AF was poor. In contrast, the IRN feature was acceptable for guiding decisions regarding AF screening in stroke patients.

Keywords: accuracy; atrial fibrillation; screening; smartwatch; stroke; wearable.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
HR data from continuous bedside ECG monitoring (CEM) device.
Figure 2
Figure 2
Smartwatch’s cloud data processing and storage.
Figure 3
Figure 3
HR data from Fitbit Charge 5® website dashboard.
Figure 4
Figure 4
Fitbit Charge 5® location.
Figure 5
Figure 5
Data collection processes of HR recordings using continuous bedside ECG monitoring and PPG-based HR recordings from a smartwatch.
Figure 6
Figure 6
Data collection processes of irregular rhythm notification using continuous bedside ECG monitoring and PPG-based algorithm for detecting AF from a smartwatch.
Figure 7
Figure 7
Assessment health data in Fitbit app showing irregular rhythm notifications.
Figure 8
Figure 8
Participant selection and summary of results.
Figure 9
Figure 9
Scatterplots of pairs of HR measurements. (a) HR readings obtained from CEM and Fitbit Charge 5 in sinus rhythm. (b) HR readings obtained from CEM and Fitbit Charge 5 when AF is present.
Figure 10
Figure 10
Bland-Altman plot of 5-min HR readings from the CEM and Fitbit Charge 5. The green, dashed line represents the mean difference between the tested device and CEM estimates (in 5 min). The gray-shaded area represents the 95% confidence interval around the mean differences ±1.96 SDs. Dots outside the gray-shaded area correspond to extreme error values.
Figure 11
Figure 11
Box plot for the distribution of MAPE values according to AF or non-AF.
Figure 12
Figure 12
Box plot for the distribution of MAPE values according to AF or non-AF and HR ≥ 100 bpm or not.
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