Detection of Atrial Fibrillation Using PPG From Smartphone Cameras (FLASH AF)
Detection of Atrial Fibrillation Using Photoplethysmography From Smartphone Cameras
Descripción general del estudio
Estado
Condiciones
Intervención / Tratamiento
Descripción detallada
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.
Tipo de estudio
Inscripción (Estimado)
Contactos y Ubicaciones
Estudio Contacto
- Nombre: Yosef Safi Harb, CEO
- Número de teléfono: +31 (0) 681885565
- Correo electrónico: yosef@happitech.com
Copia de seguridad de contactos de estudio
- Nombre: Amanda Marinov, Regulatory
- Número de teléfono: +359878422979
- Correo electrónico: a.marinov@happitech.com
Ubicaciones de estudio
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Arkansas
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Jonesboro, Arkansas, Estados Unidos, 72401
- Reclutamiento
- Nair Research, LLC dba Arrhythmia Research Group LLC
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Contacto:
- Kayla Rubino
- Número de teléfono: 870-340-7387
- Correo electrónico: krubino@drnairresearch.com
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Investigador principal:
- Devi Nair, Doctor
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Colorado
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Littleton, Colorado, Estados Unidos, 80210
- Reclutamiento
- South Denver Cardiology
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Contacto:
- Kathy Siegel, Clinical Research Director
- Número de teléfono: 720-217-6139
- Correo electrónico: ksiegel@southdenver.com
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Investigador principal:
- Srikanth Sundaram, Doctor
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Louisiana
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New Orleans, Louisiana, Estados Unidos, 70112
- Aún no reclutando
- Tulane University
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Contacto:
- Kunal Sameer, Associate Director of Ops
- Número de teléfono: 203-285-5666
- Correo electrónico: ksameer@tulane.edu
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Investigador principal:
- Nassair Marrouchi, Doctor
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Oklahoma
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Oklahoma City, Oklahoma, Estados Unidos, 73134
- Reclutamiento
- CardioVascular Health Clinic
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Contacto:
- Sophie Haynes, Regulatory Director
- Número de teléfono: 405-696-0007
- Correo electrónico: sophie@hightowerclinical.com
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Investigador principal:
- Monica Lo, Doctor
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Overijssel
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Zwolle, Overijssel, Países Bajos, 8025 AB
- Reclutamiento
- Isala Zwolle
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Contacto:
- Fleur van Haveren, Research Cardiology
- Número de teléfono: 088 6248377
- Correo electrónico: f.van.haveren@isala.nl
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Investigador principal:
- Sebastien Krul, Doctor
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Criterios de participación
Criterio de elegibilidad
Edades elegibles para estudiar
- Niño
- Adulto
- Adulto Mayor
Acepta Voluntarios Saludables
Método de muestreo
Población de estudio
Descripción
Inclusion Criteria:
- Adults aged 22 years or older
- Owns a smartphone and knows how to operate and navigate different applications.
- Individuals able to read, understand, and sign the consent form.
- Cardiology patients consulting the cardiac outpatient clinic.
- History of persistent AF or other cardiac rhythm
Exclusion Criteria:
- Participants with cognitive impairments
- Individuals who cannot read, speak, and/or understand English
- 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
Plan de estudios
¿Cómo está diseñado el estudio?
Detalles de diseño
Cohortes e Intervenciones
Grupo / Cohorte |
Intervención / Tratamiento |
|---|---|
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Sinus Rhythm
Patient visiting the Cardiology Clinic in Sinus Rhythm
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12 Lead ECG is compared to a smartphone based PPG
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Atrial Fibrillation
Patient visiting the Cardiology Clinic in Atrial Fibrillation
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12 Lead ECG is compared to a smartphone based PPG
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Other
Patient visiting the Cardiology Clinic with neither Sinus Rhythm or Atrial Fibrillation
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12 Lead ECG is compared to a smartphone based PPG
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¿Qué mide el estudio?
Medidas de resultado primarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
|---|---|---|
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To evaluate the sensitivity and specificity of the Heart Rhythm Software
Periodo de tiempo: Through study completion, an average of 6 months
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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
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Medidas de resultado secundarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
|---|---|---|
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Sensitivity & Specificity across subgroups
Periodo de tiempo: through study completion, an average of 6 months
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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.
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through study completion, an average of 6 months
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Colaboradores e Investigadores
Patrocinador
Fechas de registro del estudio
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Finalización primaria (Estimado)
Finalización del estudio (Estimado)
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Publicado por primera vez (Actual)
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Última verificación
Más información
Términos relacionados con este estudio
Palabras clave
Términos MeSH relevantes adicionales
Otros números de identificación del estudio
- HAPP-CTP-FDA-2025-002
Plan de datos de participantes individuales (IPD)
¿Planea compartir datos de participantes individuales (IPD)?
Información sobre medicamentos y dispositivos, documentos del estudio
Estudia un producto farmacéutico regulado por la FDA de EE. UU.
Estudia un producto de dispositivo regulado por la FDA de EE. UU.
producto fabricado y exportado desde los EE. UU.
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