Detection of Sleep Apnea Using Smartphone-Embedded Inertial Measurement Unit

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Abstract

Background: We previously demonstrated that sleep apnea (SA) can be detected using acceleration and gyroscope signals from an inertial measurement unit (IMU) embedded in a wristwatch device. This study aimed to explore whether an IMU embedded in non-wristwatch devices, such as smartphones, can also be used to detect SA, when worn during sleep. Methods: During polysomnography (PSG) examinations, patients wore an IMU-embedded GPS device (Amue Link®) and/or smartphones (Xperia® or iPhone®) on their abdomen. Triaxial acceleration and gyroscope signals from the IMU of each device were recorded overnight. The data were divided into training and test groups in a 2:1 ratio. An algorithm to extract respiratory movements (0.13-0.70 Hz) and detect respiratory events was developed using the training group and its performance was validated in the test group. Results: The estimated respiratory event frequency from the IMU signals of Amue Link, Xperia, and iPhone correlated with the PSG apnea-hypopnea index (AHI), with correlation coefficients of 0.90, 0.93, and 0.96, respectively, in the test group. Using cutoff values derived from the training groups, moderate-to-severe SA (AHI ≥15) was identified with areas under the receiver-operating characteristic curve of 0.95, 0.98, and 0.94, and accuracies of 87%, 94%, and 92%, respectively, in the test groups. Conclusions: SA can be quantitatively detected by IMUs embedded in non-wristwatch devices, including smartphones, when worn during sleep.

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