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Validation of a wearable cuff-less wristwatch-type blood pressure monitoring device.


ABSTRACT: Ambulatory blood pressure (BP) monitoring is recommended to improve the management of hypertension. Here, we investigated the accuracy of BP estimated using a wearable cuff-less device, InBodyWATCH, compared with BP measured using a manual sphygmomanometer. Thirty-five adults were enrolled (age 57.1 ± 17.9 years). The BP was estimated using InBodyWATCH with an individualized estimation based on a neural network model. Three paired sets of BPs from the two devices were compared using correlation analysis and Bland-Altman plots (n = 105 paired BP readings). The correlations for both systolic and diastolic BP (SBP and DBP) between the two devices were high (r = 0.964 and 0.939, both P < 0.001). The mean difference was 2.2 ± 6.1 mmHg for SBP and -0.2 ± 4.2 mmHg for DBP; these were not significant (P = 0.472 for SBP and P = 0.880 for DBP). The proportions of estimated SBP/DBP obtained from the InBodyWATCH within ± 5 mmHg of manual SBP/DBP were 71.4%/83.8%; within ± 10 mmHg they were 86.7%/98.1%; and within ± 15 mmHg they were 97.1%/99.0%. The estimated BP from this wearable cuff-less device correlated highly with the manual BP and showed good accuracy, suggesting its potential to be used in ambulatory BP monitoring.

SUBMITTER: Moon JH 

PROVIDER: S-EPMC7642418 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Validation of a wearable cuff-less wristwatch-type blood pressure monitoring device.

Moon Joon Ho JH   Kang Myung-Kyun MK   Choi Chang-Eun CE   Min Jeonghee J   Lee Hae-Young HY   Lim Soo S  

Scientific reports 20201104 1


Ambulatory blood pressure (BP) monitoring is recommended to improve the management of hypertension. Here, we investigated the accuracy of BP estimated using a wearable cuff-less device, InBodyWATCH, compared with BP measured using a manual sphygmomanometer. Thirty-five adults were enrolled (age 57.1 ± 17.9 years). The BP was estimated using InBodyWATCH with an individualized estimation based on a neural network model. Three paired sets of BPs from the two devices were compared using correlation  ...[more]

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