SPHYNCS: Feasibility of long-term monitoring with Fitbit smartwatches in central disorders of hypersomnolence and extraction of digital biomarkers in narcolepsy.

Gnarra, Oriella; van der Meer, Julia; Warncke D, Jan; Fregolente, Livia G; Wenz, Elena; Zub, Kseniia; Nwachukwu, Uchendu; Zhang, Zhongxing; Khatami, Ramin; von Manitius, Sigrid; Miano, Silvia; Acker, Jens; Strub, Mathias; Riener, Robert; Bassetti, Claudio L. A.; Schmidt, Markus H (2024). SPHYNCS: Feasibility of long-term monitoring with Fitbit smartwatches in central disorders of hypersomnolence and extraction of digital biomarkers in narcolepsy. (In Press). Sleep Oxford University Press 10.1093/sleep/zsae083

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The Swiss Primary Hypersomnolence and Narcolepsy Cohort Study (SPHYNCS) is a multicenter research initiative to identify new biomarkers in central disorders of hypersomnolence (CDH). Whereas narcolepsy type 1 (NT1) is well characterized, other CDH disorders lack precise biomarkers. In SPHYNCS, we utilized Fitbit smartwatches to monitor physical activity, heart rate, and sleep parameters over one year. We examined the feasibility of long-term ambulatory monitoring using the wearable device. We then explored digital biomarkers differentiating patients with NT1 from healthy controls (HC). A total of 115 participants received a Fitbit smartwatch. Using a compliance metric to evaluate the usability of the wearable device, we found an overall compliance rate of 80% over one year. We calculated daily physical activity, heart rate, and sleep parameters from two weeks of greatest compliance to compare NT1 (n=20) and HC (n=9) subjects. Compared to controls, NT1 patients demonstrated findings consistent with increased sleep fragmentation, including significantly greater wake-after-sleep onset (p=0.007) and awakening index (p=0.025), as well as standard deviation of time in bed (p=0.044). Moreover, NT1 patients exhibited a significantly shorter REM latency (p=0.019), and sleep latency (p=0.001), as well as a lower peak heart rate (p=0.008), heart rate standard deviation (p=0.039) and high-intensity activity (p=0.009) compared to HC. This ongoing study demonstrates the feasibility of long-term monitoring with wearable technology in patients with CDH and potentially identifies a digital biomarker profile for NT1. While further validation is needed in larger datasets, these data suggest that long-term wearable technology may play a future role in diagnosing and managing narcolepsy.

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