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适用于所有高血压类型的人工智能无袖带无创连续血压监测仪的研发与内部验证

Development and Internal Validation of an AI-Enabled Cuff-less, Non-invasive Continuous Blood Pressure Monitor Across All Classes of Hypertension.

作者信息

Lopez-Jimenez Francisco, Deshmukh Abhishek, Bisognano John, Boehmer John, Ramasamy Mouli, Shyam Kumar Prashanth, Kapa Suraj, Varadan Venk, Varadan Vijay, Fudim Marat

机构信息

Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, 55905, USA.

Department of Internal Medicine, Department of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA.

出版信息

J Cardiovasc Transl Res. 2025 Apr;18(2):280-290. doi: 10.1007/s12265-024-10589-5. Epub 2025 Jan 13.

Abstract

BACKGROUND

Non-invasive, continuous blood pressure monitoring technologies require additional validation beyond standard cuff-based methods. This study evaluates a non-invasive, multiparametric wearable cuffless blood pressure (BP) diagnostic monitor across all hypertension classes with diverse subjects.

METHODS

A prospective, multicenter study assessed Nanowear's SimpleSense-BP performance, including induced and natural BP changes, significant BP variations (Systolic BP (SBP) ≥ ± 15 mm Hg and Diastolic BP (DBP) ≥ ± 10 mm Hg), and reference input value validity over 4 weeks.

RESULTS

303 subjects (18-83 yrs; 50.16% Female) participated in algorithmic development and validation (Normal - 35%, Prehypertensive - 24%, Stage 1 - 24%, Stage 2 - 17%). 54 subjects were tested for induced change performance, 149 exhibited significant changes, and 91 validated reference value duration.

CONCLUSIONS

The study clinically validated a continuous, AI-based BP diagnostic monitor using non-invasive wearable data. Further testing on diverse populations and external validation are recommended. The protocol was inspired by ISO 81060-2 and IEEE 1708:2019 standards.

摘要

背景

非侵入性连续血压监测技术需要在基于标准袖带的方法之外进行额外验证。本研究评估了一种非侵入性多参数可穿戴无袖带血压(BP)诊断监测仪在各类高血压患者及不同受试者中的性能。

方法

一项前瞻性多中心研究评估了Nanowear公司的SimpleSense-BP的性能,包括诱导性和自然性血压变化、显著血压波动(收缩压(SBP)≥±15 mmHg和舒张压(DBP)≥±10 mmHg)以及4周内参考输入值的有效性。

结果

303名受试者(年龄18 - 83岁;50.16%为女性)参与了算法开发和验证(正常 - 35%,高血压前期 - 24%,1期 - 24%,2期 - 17%)。54名受试者接受了诱导性变化性能测试,149名表现出显著变化,91名验证了参考值持续时间。

结论

该研究在临床上验证了一种基于人工智能的连续血压诊断监测仪,其使用非侵入性可穿戴数据。建议对不同人群进行进一步测试和外部验证。该方案受ISO 81060 - 2和IEEE 1708:2019标准启发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17bf/12043788/9f53b02d736f/12265_2024_10589_Fig1_HTML.jpg

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