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Detection of Atrial Fibrillation Using PPG From Smartphone Cameras (FLASH AF)

2026年8月19日 更新者：Happitech BV

Detection of Atrial Fibrillation Using Photoplethysmography From Smartphone Cameras

The protocol is designed to enroll patients from at least 3 diverse clinical sites with smartphones who are being evaluated for the presence or absence of atrial fibrillation (AF) using the Heart Rhythm Software algorithm running on their smartphones. Algorithm output will be compared to a gold standard of 12-lead ECG recorded with a simultaneous PPG measurement.

研究概览

地位

招聘中

条件

干预/治疗

详细说明

Atrial fibrillation (AF) is the most common sustained arrhythmia worldwide, and its prevalence is increasing and is expected to continue increasing for decades,. Detection of AF episodes may be useful for the identification of undiagnosed AF and in making clinical management decisions that include oral anticoagulation, restoration and maintenance of sinus rhythm, control of ventricular rate, and risk factor modification. Treatment of AF is associated with improvements of quality of life, stroke prevention, and reduced risk of heart failure.

Traditionally, diagnosis of AF is done using an electrocardiogram, with low amplitude or absent p-waves and narrow complex "irregularly irregular" pattern intervals seen on the ECG,. After diagnosis, there are a variety of methods that can be used to manage AF. Ambulatory ECG monitoring, implantable monitoring devices, and over-the-counter wrist-worn devices have been used to manage patients with AF,,. However, these devices are inconvenient and expensive which limits their wide adoption into clinical practice. There is an unmet clinical need for an easy to use and inexpensive over-the-counter FDA-cleared products that can detect episodes of AF in real-time and notify patients to seek out further care when AF is suspected.

Recent technological advancements have allowed for the identification of AF using smartwatches, with device manufacturers gaining over-the-counter regulatory clearance for their irregular heart rate detection algorithms,. These wrist-worn devices use a light-based measurement method called photoplethysmography (PPG) to measure changes in light absorbance and reflectance to understand changes in blood flow in superficial vasculature. The waveform generated from this measurement can be used to measure parameters like pulse rate, respiratory rate, pulse rate variability and others in addition to detecting AF. The increasing ubiquity of smartphones worldwide has led to greater availability of heart rhythm diagnostics using smartphone photoplethysmography (PPG). Smartphone camera PPG technology uses the light-emitting diode in cameras to measure pulsatile changes in light intensity that are reflected from a finger and can be used to detect AF. The widespread availability of this technology has the potential to improve the accessibility and convenience of heart rhythm monitoring, particularly in remote or underserved areas. This could result in improvements in early detection and management of AF, leading to better patient outcomes. Several smartphone PPG-based algorithms have been developed that utilize smartphones' built-in cameras to detect AF. The sensitivity and specificity of these algorithms for the detection of AF range between 81%-100% and 85%-100% respectively. However, there is a lack of evidence regarding the performance of these algorithms in detecting AF in an out-of-hospital setting using a gold-standard reference.

Happitech has developed a proprietary software development kit (SDK) that can be utilized to measure patients' cardiovascular parameters and identify potential pathologies including AF. Happitech's algorithm requires users to place a digit directly against their phone camera, and the camera and underlying algorithm detect subtle differences in blood flow to calculate physiological parameters for monitoring and clinical use.

The purpose of this study is to validate the performance of Happitech's PPG-based algorithm for the detection of AF against a 12-lead ECG in a diverse population of patients including cardiology patients being evaluated as inpatients or at a cardiology clinic visit.

研究类型

观察性的

注册 (估计的)

554

联系人和位置

本节提供了进行研究的人员的详细联系信息，以及有关进行该研究的地点的信息。

学习联系方式

研究联系人备份

学习地点

  • 美国
    • Arkansas
      • Jonesboro、Arkansas、美国、72401
        • 招聘中
        • Nair Research, LLC dba Arrhythmia Research Group LLC
        • 接触：
        • 首席研究员：
          • Devi Nair, Doctor
    • Colorado
      • Littleton、Colorado、美国、80210
        • 招聘中
        • South Denver Cardiology
        • 接触：
        • 首席研究员：
          • Srikanth Sundaram, Doctor
    • Louisiana
      • New Orleans、Louisiana、美国、70112
        • 尚未招聘
        • Tulane University
        • 接触：
          • Kunal Sameer, Associate Director of Ops
          • 电话号码：203-285-5666
          • 邮箱：ksameer@tulane.edu
        • 首席研究员：
          • Nassair Marrouchi, Doctor
    • Oklahoma
      • Oklahoma City、Oklahoma、美国、73134
        • 招聘中
        • CardioVascular Health Clinic
        • 接触：
        • 首席研究员：
          • Monica Lo, Doctor
  • 荷兰
    • Overijssel
      • Zwolle、Overijssel、荷兰、8025 AB
        • 招聘中
        • Isala Zwolle
        • 接触：
        • 首席研究员：
          • Sebastien Krul, Doctor

参与标准

研究人员寻找符合特定描述的人，称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

  • 孩子
  • 成人
  • 年长者

接受健康志愿者

不

取样方法

非概率样本

研究人群

Male and female patients aged 22 years or older who are cardiology patients consulting the cardiac outpatient clinic, 50% of whom have a rhythm of atrial fibrillation at the time of enrollment, and own a smartphone.

描述

Inclusion Criteria:

  1. Adults aged 22 years or older
  2. Owns a smartphone and knows how to operate and navigate different applications.
  3. Individuals able to read, understand, and sign the consent form.
  4. Cardiology patients consulting the cardiac outpatient clinic.
  5. History of persistent AF or other cardiac rhythm

Exclusion Criteria:

  1. Participants with cognitive impairments
  2. Individuals who cannot read, speak, and/or understand English
  3. Patients with implantable neurostimulators, cardiac implantable device in an atrial or ventricular paced rhythm documented on a 12-lead ECG during the initial study visit

学习计划

本节提供研究计划的详细信息，包括研究的设计方式和研究的衡量标准。

研究是如何设计的？

设计细节

队列和干预

团体/队列
干预/治疗
Sinus Rhythm
Patient visiting the Cardiology Clinic in Sinus Rhythm
诊断测试：12 Lead ECG is compared to a smartphone based PPG
12 Lead ECG is compared to a smartphone based PPG
Atrial Fibrillation
Patient visiting the Cardiology Clinic in Atrial Fibrillation
诊断测试：12 Lead ECG is compared to a smartphone based PPG
12 Lead ECG is compared to a smartphone based PPG
Other
Patient visiting the Cardiology Clinic with neither Sinus Rhythm or Atrial Fibrillation
诊断测试：12 Lead ECG is compared to a smartphone based PPG
12 Lead ECG is compared to a smartphone based PPG

研究衡量的是什么？

主要结果指标

结果测量
措施说明
大体时间
To evaluate the sensitivity and specificity of the Heart Rhythm Software
大体时间：Through study completion, an average of 6 months

To evaluate the sensitivity and specificity of the Heart Rhythm Software algorithm running on a commercially available smartphone to detect atrial fibrillation segments using photoplethysmography (PPG) as measured through the phone's camera.

Se is defined as the percentage of patients with 90 second interval recordings scored by the Heart Rhythm Software algorithm as AF, out of all intervals determined by the Clinical Adjudication Committee (CAC) to be AF (gold standard).

Sp is defined as the percentage of patients with 90 second intervals scored by the Heart Rhythm Software algorithm as NSR out of all ECG recordings determined by the CAC to be NSR.
Through study completion, an average of 6 months

次要结果测量

结果测量
措施说明
大体时间
Sensitivity & Specificity across subgroups
大体时间：through study completion, an average of 6 months
The accuracy of the Happitech Heart Rhythm Software algorithm in detecting irregular rhythm suspected of AF and regular rhythm suspected normal sinus rhythm will be further investigated in subgroups defined by ethnicity, race, BMI, age group, smartphone type, and Fitzpatrick scale score. The sensitivity and specificity will be presented as an estimate and associated 95% CI's, as well as a Chi-square or Fisher's Exact p-value to assess if all levels of the subgroup are homogeneous.
through study completion, an average of 6 months

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

赞助

Happitech BV

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查，以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2026年6月30日

初级完成 (估计的)

2026年11月1日

研究完成 (估计的)

2026年11月1日

研究注册日期

首次提交

2026年8月11日

首先提交符合 QC 标准的

2026年8月19日

首次发布 (实际的)

2026年8月21日

研究记录更新

最后更新发布 (实际的)

2026年8月21日

上次提交的符合 QC 标准的更新

2026年8月19日

最后验证

2026年8月1日

更多信息

与本研究相关的术语

关键字

其他相关的 MeSH 术语

其他研究编号

  • HAPP-CTP-FDA-2025-002

计划个人参与者数据 (IPD)

计划共享个人参与者数据 (IPD)？

未定

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

是的

在美国制造并从美国出口的产品

不

此信息直接从 clinicaltrials.gov 网站检索，没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求，请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改，我们的网站上也会自动更新.

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