Atrial Fibrillation Screening With Photo-plethysmography Through a Smartphone Camera

Frederik H. Verbrugge; Tine Proesmans; Johan Vijgen; Wilfried Mullens; Maximo Rivero-Ayerza; Hugo Van Herendael; Pieter Vandervoort; Dieter Nuyens


Europace. 2019;21(8):1167-1175. 

In This Article


Study Design

This cross-sectional screening study was set up by Qompium N.V. (Hasselt, Belgium) in cooperation with the academic authors. The aim was to assess the feasibility of mass screening for AF through a smartphone-based algorithm using PPG technology. A local newspaper in Layman's press agreed to cover an article to create awareness and inform its readers on AF and the potential value of screening for this arrhythmia. With 92 638 subscribers in 2017, this newspaper served ~10.8% of the local community at the time the article was published in print as well as online (September 2017). Readers were enlightened about the possibility of screening for AF by making use of the camera in their smartphone. A QR-code was provided to give free access to the screening application for a 7-day period (Figure 1). Additionally, the article comprised instructions on how to install the application, perform measurements with it, and participate in the screening programme. Prior to account activation or any data collection, users were informed and asked to agree with the privacy policy and terms of service of the company. Study participants were instructed to assess their heart rhythm twice daily, as well as in case of any symptoms. Notifications were sent through the application to boost compliance towards the recommended screening frequency. After termination of the screening period, accounts were closed, and users received a summarizing report by e-mail. This summarizing report contained information on the number and quality of heart rhythm measurements performed, the highest, lowest, and average heart rate registered, as well as any irregularities identified. All participants with episodes other than a normal regular heart rhythm were advised to see their general practitioner to consider the need for further evaluation and additional testing. The study complies with the Declaration of Helsinki. All authors had full access to the data and vouch for its accuracy and completeness. The first author (F.V.) wrote the first draft of the manuscript, which was subsequently revised by all authors.

Figure 1.

(A) Scanning of the QR-code and registration. (B) On-screen instructions guide the user to perform high-quality measurements. During the measurement, a screen is displayed with a countdown clock and a real-time photo-plethysmography trace. After each measurement, well-being and symptoms can be annotated. (C) Correct position to acquire a reliable photo-plethysmography signal. (D) Each measurement is automatically analysed by the algorithm. Measurements indicative of an irregular rhythm are reviewed by medical technicians under supervision of cardiologists. A summarizing report includes an overview of the measurements and a general conclusion.

Smartphone-based Photo-plethysmography Signal Acquisition

To assess the heart rhythm in this study, PPG technology was applied. Photo-plethysmography is a technique whereby a volumetric measurement is optically obtained. A classic application is the pulse oximeter, which illuminates the skin and measures changes in light absorption with blood volume pulse variation, using this information to determine oxygen saturation and heart rhythm.[13] The same principle can be applied by using the flashlight of a smartphone and measuring the amount of reflected light through its build-in camera. A CE and FDA approved application has been developed for this purpose and can be used with most commercially available devices.[12] To obtain a high-quality PPG signal with a smartphone, subjects should adopt a sitting position with both arms resting on a firm surface, holding the smartphone in a vertical position with their dominant hand. Subsequently, the index finger of their non-dominant hand should cover the flashlight and backside camera horizontally, without putting firm pressure (Figure 1). The measurement time to acquire the PPG signal is ~1 min, with a countdown clock visible on the smartphone screen when the application is running (Figure 1).

Smartphone Application to Assess the Heart Rhythm

The smartphone application used in this study firstly checks acquired PPG signals for their quality. Insufficient quality is identified using a machine-learning algorithm based on a recurrent neural network. Compromised signals are not used for analysis to avoid inaccurate diagnostic results. In this study, the number of insufficient quality measurements was closely monitored. Study participants with frequent poor-quality PPG measurements received notifications through the application, guiding them on how to perform better measurements. After every measurement, the user is asked to indicate his/her well-being on a 5-point Likert scale and comment on the potential presence of symptoms (i.e. light headedness, confusion, fatigue, palpitations, chest pain, shortness of breath, and/or other symptoms). Afterwards, a screen shows up that displays the average heart rate and any irregularities detected. A text with corresponding colour code is used to communicate results to the user: measurement of insufficient quality (blue), normal heart rhythm (green), or possible irregularities (orange). The last category is divided by the algorithm in suspected premature or missed beats (i.e. ≥3 during the 1-min registration) vs. suspected AF or atrial flutter with variable heart block. The AF algorithm is a random tree classifier using a combination of different features that analyse inter and intra beat-to-beat characteristics and time resolved and dimensionless patterns.

The distinction between irregular measurements was only communicated to the study participant through the final report after all divergent PPG signals had undergone offline secondary analysis by medical technicians, to ensure data quality and avoid concern about potentially false positive alarms (Figure 1). Notably, as PPG signals reflect pulse pressure, atrial flutter with constant heart block, or regular atrial tachycardia cannot be distinguished from sinus rhythm by the application, unless the presence of arrhythmia is clear because of the high ventricular rate.

Data Collection

At the time of account creation for participation to the screening programme, subscribers were required to register age and gender. In addition, it was asked to voluntarily provide length and body weight. Other data collected include the timing, results, and raw PPG data for every use of the smartphone application for heart rhythm assessment as described above. Results were automatically sent to a secure server by the application and subsequently de-identified for all analyses. Raw PPG data for all suspected irregularities underwent secondary offline review by medical technicians under the supervision of cardiologists experienced in PPG analysis. The final diagnosis was confirmed by consensus.

Patient-reported Outcomes

Four months after communicating the results and call-to-action in the end-report, screen-positive participants were contacted by phone to collect clinical outcome data.

Statistical Analysis

Continuous variables are expressed as mean ± standard deviation. The independent Student's t-test was used for comparison between individuals with vs. without AF. Categorical data are expressed as counts (%) and compared with Pearson's χ 2 test. Statistical significance was always set at a two-tailed probability level of <0.05. All statistics were performed using R Statistical Software (version 3.5.1) and RStudio (version 1.1.447) (Boston, MA, USA).