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Updated: Jun 13, 2026

Multi-Modal Home Sleep Monitoring in Older Adults
Published on: January 26, 2019
External validation of a fingertip wearable device for obstructive sleep apnea diagnosis and split-night tracking of
Ke-Wei Chen1, Aatif M Husain2, David M Rapoport3
1PranaQ Pte. Ltd., 9 Straits View, #05-07, Marina One West Towers, 018937, Singapore.
Study Objectives:
To externally validate a novel Type IV fingertip wearable device, TipTraQ, against polysomnography (PSG) for diagnosing obstructive sleep apnea (OSA) in the western-country population with both AASM AHI1A(3%) and AHI1B(4%) labeling rules. Furthermore, evaluate its ability to dynamically track positive airway pressure (PAP) treatment effectiveness using split-night titration as surrogate with short-term apnea-hypopnea index (AHI) and TipTraQ-derived Respiratory Events Index (TQ-REI) sequences.
Methods:
In a prospective study at the Duke Sleep Disorders Center, 198 participants were enrolled, including a diagnostic validation cohort (n = 147) and a split-night titration cohort (n = 29). Short-term AHI and TQ-REI sequences were calculated using a 15-min moving window updated every 5 min to capture respiratory event dynamics. Agreement between TipTraQ and PSG was evaluated using standard performance metrics.
Results:
In the diagnostic cohort, TipTraQ correlated strongly with PSG for total sleep time (TST; PCC = 0.786) and REM duration (PCC = 0.655). Bland-Altman analysis revealed mean biases of -9.50 min for TST and -9.46 min for REM. Epoch-by-epoch sleep staging (Wake, REM, Non-REM) yielded a Cohen's Kappa of 0.567, with highest sensitivity in non-REM sleep (0.824). TQ-REI correlated highly with AHI under AASM scoring rules (PCC = 0.879 for 1A; 0.910 for 1B). In the titration cohort, TipTraQ maintained consistent performance. Analysis of short-term AHI and TQ-REI sequences demonstrated the device's ability to track respiratory event dynamics, yielding a median PCC of 0.882 (1A) and 0.872 (1B).
Conclusion:
TipTraQ shows strong agreement with PSG for respiratory metrics and moderate agreement with PSG for sleep metrics, and captures temporal dynamics of sleep-disordered breathing events.
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