Abstract

Rapid advances in cuffless blood pressure (BP) monitoring over the last decade have the potential to radically transform clinical care for cardiovascular health. However, due to the large heterogeneity in device design and evaluation, it is difficult to critically and quantitatively evaluate research progress in cuffless BP monitoring. In this two-part manuscript, we seek to provide a principled way of describing and accounting for the heterogeneity in device and study design. We first provide an overview of foundational elements and design principles of three critical aspects in the pipeline: 1) sensors and systems, 2) pre-processing and feature extraction, and 3) BP estimation algorithms. Then, we critically analyze the state-of-theart methods via a systematic review. We find a large amount of heterogeneity in study designs making fair comparisons challenging. In addition, many study designs lead to data leakage, and underpowered studies. We suggest a first opencontribution BP estimation benchmark based on existing public datasets for standardized algorithmic comparisons. Second, we observe that BP distribution in the study sample and the time between calibration and test in emerging personalized devices are significant confounders in BP estimation error. We suggest accounting for these using a metric "explained deviation" which is closely related to the coefficient of determination (R2, a frequently used statistic). Finally, we complement this manuscript with a website, https://wearablebp.github.io, containing a bibliography, meta-analysis results, datasets, and benchmarks, providing a timely platform to understand the state-of-the-art devices. There is large heterogeneity in device and study design, which should be carefully accounted for when designing, comparing, and contrasting studies. Our findings will allow readers to parse out the heterogeneous literature and move toward promising directions for safer and more reliable devices in clinical practice and beyond.

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