Objective The Hilbert- Huang transformation (HHT) method was introduced to process the bio-impedance gastric motility signals from subjects.Methods Nonlinear and non-stationary original gastric motility series were decomposed into a number of intrinsic mode function (1MF) components by the empirical mode decomposition method (EMD).Hilbert transformation was carried out then and instantaneous frequency was extracted effectively.Gastric motility signal among 0.03-0.06 Hz was reconstructed from the IMF.Results The results suggested that HHT was a new and applicable time series analysis method based on mode decomposition and could extract impedance signal and remove the disturbances such as blood flow and breathing.Conclusion The new adaptive mode decomposition-based signal processing method provides a new method to investigate clinical gastric motility information.

Objective To evaluate the role of distortion product otoacoustic emissions (DPOAE) testing in evaluating early hearing loss among noise-exposed workers. Methods A total of 174 noise-exposed workers in a metal shipbuilding enterprise were selected as the research subjects by the convenience sampling method. Pure tone audiometry (PTA), DPOAE and the level of noise exposure were conducted on the workers. The rank correlation analysis was used to analyze the correlation between DPOAE amplitude and PTA threshold. The multilevel model was used to analyze the effects of gender, age, noise exposure intensity, cumulative noise exposure (CNE), hearing loss classification and PTA threshold on DPOAE results. Results At the frequencies of 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00 kHz, the DPOAE amplitude was negatively correlated with the PTA threshold (rank correlation coefficients were -0.12, -0.48, -0.47, -0.18, -0.23, -0.44, -0.19, respectively, all P<0.01). At the most frequencies, DPOAE amplitude was negatively correlated with age and CNE (all P<0.05). The results of multilevel model analysis showed that there were significant differences in DPOAE amplitudes at certain frequencies across gender, age, noise intensity, CNE, and hearing loss classification (all P<0.05). Significant differences in DPOAE responses were found among different CNE and hearing loss groups (all P<0.01). Conclusion DPOAE testing can objectively reflect the hearing status of noise-exposed workers and could be considered for inclusion in routine hearing monitoring to facilitate early detection of noise-induced hearing loss.