Wavelet analysis of overnight airflow to detect obstructive sleep apnea in children

Producción CientíficaThis study focused on the automatic analysis of the airflow signal (AF) to aid in the diagnosis of pediatric obstructive sleep apnea (OSA). Thus, our aims were: (i) to characterize the overnight AF characteristics using discrete wavelet transform (DWT) approach, (ii) to evaluate its diagnostic utility, and (iii) to assess its complementarity with the 3% oxygen desaturation index (ODI3). In order to reach these goals, we analyzed 946 overnight pediatric AF recordings in three stages: (i) DWT-derived feature extraction, (ii) feature selection, and (iii) pattern recognition. AF recordings from OSA patients showed both lower detail coefficients and decreased activity associated with the normal breathing band. Wavelet analysis also revealed that OSA disturbed the frequency and energy distribution of the AF signal, increasing its irregularity. Moreover, the information obtained from the wavelet analysis was complementary to ODI3. In this regard, the combination of both wavelet information and ODI3 achieved high diagnostic accuracy using the common OSA-positive cutoffs: 77.97%, 81.91%, and 90.99% (AdaBoost.M2), and 81.96%, 82.14%, and 90.69% (Bayesian multi-layer perceptron) for 1, 5, and 10 apneic events/hour, respectively. Hence, these findings suggest that DWT properly characterizes OSA-related severity as embedded in nocturnal AF, and could simplify the diagnosis of pediatric OSA.Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación y Fondo Europeo de Desarrollo Regional (FEDER) - (Projects DPI2017-84280-R and RTC-2017-6516-1)Comisión Europea y Fondo Europeo de Desarrollo Regional (FEDER) - (POCTEP 0702_MIGRAINEE_2_E)Instituto de Salud Carlos III y Fondo Europeo de Desarrollo Regional (FEDER) - (CIBER-BBN)Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación y Fondo Social Europeo - (grant RYC2019- 028566-I)Ministerio de Educación, Cultura y Deporte - (grant FPU16/02938)Institutes of Health - (grants HL130984, HL140548, and AG061824