Key result
MOSAIC wearable sensor predicts continuous systolic BP within ~5 mmHg error compared to cuff readings.
Why the study?
Existing blood pressure measurement methods are either invasive, tethered, or suffer from low temporal resolution, leaving non-invasive continuous blood pressure estimation a significant challenge.
Does the wearable multi-modal sensor array (MOSAIC) accurately estimate continuous cuffless systolic and diastolic blood pressure compared to standard cuff measurements in adult subjects during various physical and physiological maneuvers?
Observational (n=16)
Open-label
No
Does the wearable multi-modal sensor array (MOSAIC) accurately estimate continuous cuffless systolic and diastolic blood pressure compared to standard cuff measurements in adult subjects during various physical and physiological maneuvers?
This proof-of-concept study demonstrates that a distributed, multi-site wearable sensor array (MOSAIC) can continuously estimate cuffless systolic and diastolic blood pressure during routine physical activities and maneuvers with low mean absolute error.
Answers are grounded in this paper and cite their sources.
Promising for continuous ambulatory BP monitoring; leaves open clinical adoption pending larger validation studies.
Blood pressure (BP) measurement is crucial for medical care, yet existing BP methods are either invasive, tethered, or suffer from low temporal resolution. Non-invasive continuous BP estimation thus remains a significant challenge. To address these challenges, this work presents a novel, non-invasive, multi-modal sensor designed for continuous blood pressure estimation using multiple biosignal modalities as feature inputs. From these input data, we extract cardiovascular timing intervals (e.g., pulse arrival time), which serve as key features for BP regression models, enabling continuous, non-invasive BP monitoring. We validate our algorithm with 16 healthy subjects using standard blood pressure cuff readings as ground truth. Our wearable, non-invasive multimodal and multinodal sensor array for integrated computation (MOSAIC) demonstrated promising performance and was able to predict systolic and diastolic BP across all study subjects with a MAE of 5.31 ± 7.32 mmHg and 4.27 ± 2.35 mmHg, respectively.
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Rattray et al. (2026) conducted an observational in Blood pressure monitoring / Hypertension (n=16). Wearable multimodal and multinodal sensor array for integrated computation (MOSAIC) vs. Standard blood pressure cuff was evaluated on Mean absolute error (MAE) of systolic and diastolic blood pressure estimation compared to standard cuff readings (SBP MAE 5.31 ± 7.32 mmHg; DBP MAE 4.27 ± 2.35 mmHg). The MOSAIC wearable sensor array predicted continuous systolic and diastolic blood pressure with a mean absolute error of 5.31 ± 7.32 mmHg and 4.27 ± 2.35 mmHg compared to cuff readings.
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