Screening for obstructive sleep apnea with novel hybrid acoustic smartphone app technology (Tiron, Lyon, Shouldice et al., J Thorac Dis 2020)

Roxana Tiron, Graeme Lyon, Hannah Kilroy, Ahmed Osman, Nicola Kelly, Niall O'Mahony, Cesar Lopes, Sam Coffey, Stephen McMahon, Michael Wren, Kieran Conway, Niall Fox, John Costello, Redmond Shouldice (ResMed Sensor Technologies, Dublin); Katharina Lederer, Ingo Fietze, Thomas Penzel (Advanced Sleep Research, Berlin). Open HTML: jtd.amegroups.org/article/view/42773/html. Licence: journal is open; treat quotation as CC-style OA with attribution (confirm publisher licence on reuse).

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BackgroundObstructive sleep apnea (OSA) has a high prevalence, with an estimated 425 million adults with apnea hypopnea index (AHI) of ≥15 events/hour, and is significantly underdiagnosed. This presents a significant pain point for both the sufferers, and for healthcare systems, particularly in a post COVID-19 pandemic world. As such, it presents an opportunity for new technologies that can enable screening in both developing and developed countries. In this work, the performance of a non-contact OSA screener App that can run on both Apple and Android smartphones is presented.MethodsThe subtle breathing patterns of a person in bed can be measured via a smartphone using the "Firefly" app technology platform [and underpinning software development kit (SDK)], which utilizes advanced digital signal processing (DSP) technology and artificial intelligence (AI) algorithms to identify detailed sleep stages, respiration rate, snoring, and OSA patterns. The smartphone is simply placed adjacent to the subject, such as on a bedside table, night stand or shelf, during the sleep session. The system was trained on a set of 128 overnights recorded at a sleep laboratory, where volunteers underwent simultaneous full polysomnography (PSG), and "Firefly" smartphone app analysis. A separate independent test set of 120 recordings was collected across a range of Apple iOS and Android smartphones, and withheld for performance evaluation by a different team. An operating point tuned for mid-sensitivity (i.e., balancing sensitivity and specificity) was chosen for the screener.ResultsThe performance on the test set is comparable to ambulatory OSA screeners, and other smartphone screening apps, with a sensitivity of 88.3% and specificity of 80.0% [with receiver operating characteristic (ROC) area under the curve (AUC) of 0.92], for a clinical threshold for the AHI of ≥15 events/hour of detected sleep time.ConclusionsThe "Firefly" app based sensing technology offers the potential to significantly lower the barrier of entry to OSA screening, as no hardware (other than the user's personal smartphone) is required. Additionally, multi-night analysis is possible in the home environment, without requiring the wearing of a portable PSG or other home sleep test (HST).

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