False Atrial Fibrillation Alerts from Smartwatches are Associated with Decreased Perceived Physical Well-being and Confidence in Chronic Symptoms Management.

Cardiology and cardiovascular medicine Pub Date : 2023-01-01 Epub Date: 2023-04-03 DOI:10.26502/fccm.92920314
Khanh-Van Tran, Andreas Filippaios, Kamran Noorishirazi, Eric Ding, Dong Han, Fahimeh Mohagheghian, Qiying Dai, Jordy Mehawej, Ziyue Wang, Darleen Lessard, Edith Mensah Otabil, Alex Hamel, Tenes Paul, Matthew F Gottbrecht, Timothy P Fitzgibbons, Jane Saczynski, Ki H Chon, David D McManus
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Abstract

Wrist-based wearables have been FDA approved for AF detection. However, the health behavior impact of false AF alerts from wearables on older patients at high risk for AF are not known. In this work, we analyzed data from the Pulsewatch (NCT03761394) study, which randomized patients (≥50 years) with history of stroke or transient ischemic attack to wear a patch monitor and a smartwatch linked to a smartphone running the Pulsewatch application vs to only the cardiac patch monitor over 14 days. At baseline and 14 days, participants completed validated instruments to assess for anxiety, patient activation, perceived mental and physical health, chronic symptom management self-efficacy, and medicine adherence. We employed linear regression to examine associations between false AF alerts with change in patient-reported outcomes. Receipt of false AF alerts was related to a dose-dependent decline in self-perceived physical health and levels of disease self-management. We developed a novel convolutional denoising autoencoder (CDA) to remove motion and noise artifacts in photoplethysmography (PPG) segments to optimize AF detection, which substantially reduced the number of false alerts. A promising approach to avoid negative impact of false alerts is to employ artificial intelligence driven algorithms to improve accuracy.

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智能手表发出的虚假心房颤动警报与身体健康感知和慢性症状管理信心下降有关。
腕式可穿戴设备已获得 FDA 批准用于房颤检测。然而,可穿戴设备发出的错误房颤警报对房颤高危老年患者健康行为的影响尚不清楚。在这项工作中,我们分析了 Pulsewatch(NCT03761394)研究的数据,该研究随机让有中风或短暂性脑缺血发作病史的患者(≥50 岁)在 14 天内佩戴贴片监测仪和与运行 Pulsewatch 应用程序的智能手机相连的智能手表,与只佩戴心脏贴片监测仪进行对比。在基线和 14 天内,参与者完成了评估焦虑、患者激活、身心健康感知、慢性症状管理自我效能和药物依从性的有效工具。我们采用线性回归法研究了错误房颤警报与患者报告结果变化之间的关联。收到虚假房颤警报与自我感觉身体健康和疾病自我管理水平的下降呈剂量依赖关系。我们开发了一种新颖的卷积去噪自动编码器(CDA),用于去除光电血压计(PPG)片段中的运动和噪声伪影,以优化房颤检测,从而大大减少了错误警报的数量。采用人工智能驱动的算法来提高准确性是避免误报负面影响的一种可行方法。
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