Biomaterial Database

Wavelet analysis of click-evoked otoacoustic emissions. 1998

G Tognola, and F Grandori, and P Ravazzani

Department of Biomedical Engineering, Polytechnic of Milan, Italy. tognola@biomed.polimi.it

Time-frequency distribution methods are being widely used for the analysis of a variety of biomedical signals. Recently, they have been applied also to study otoacoustic emissions (OAE's), the active acoustic response of the hearing end organ. Click-evoked otoacoustic emissions (CEOAE's) are time-varying signals with a clear frequency dispersion along with the time axis. Analysis of CEOAE's is of considerable interest due to their close relation with cochlear mechanisms. In this paper, several basic time-frequency distribution methods are considered and compared on the basis of both simulated signals and real CEOAE's. The particular structure of CEOAE's requires a method with both a satisfactory time and frequency resolution. Results from simulations and real CEOAE's revealed that the wavelet approach is highly suitable for the analysis of such signals. Some examples of the application of the wavelet transform to CEOAE's are provided here. Applications range from the extraction of normative data from adult and neonatal OAE's to the extraction of quantitative parameters for clinical purposes.

UI	MeSH Term	Description	Entries
D007231	Infant, Newborn	An infant during the first 28 days after birth.	Neonate,Newborns,Infants, Newborn,Neonates,Newborn,Newborn Infant,Newborn Infants
D008954	Models, Biological	Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.	Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D012016	Reference Values	The range or frequency distribution of a measurement in a population (of organisms, organs or things) that has not been selected for the presence of disease or abnormality.	Normal Range,Normal Values,Reference Ranges,Normal Ranges,Normal Value,Range, Normal,Range, Reference,Ranges, Normal,Ranges, Reference,Reference Range,Reference Value,Value, Normal,Value, Reference,Values, Normal,Values, Reference
D005071	Evoked Potentials	Electrical responses recorded from nerve, muscle, SENSORY RECEPTOR, or area of the CENTRAL NERVOUS SYSTEM following stimulation. They range from less than a microvolt to several microvolts. The evoked potential can be auditory (EVOKED POTENTIALS, AUDITORY), somatosensory (EVOKED POTENTIALS, SOMATOSENSORY), visual (EVOKED POTENTIALS, VISUAL), or motor (EVOKED POTENTIALS, MOTOR), or other modalities that have been reported.	Event Related Potential,Event-Related Potentials,Evoked Potential,N100 Evoked Potential,P50 Evoked Potential,N1 Wave,N100 Evoked Potentials,N2 Wave,N200 Evoked Potentials,N3 Wave,N300 Evoked Potentials,N4 Wave,N400 Evoked Potentials,P2 Wave,P200 Evoked Potentials,P50 Evoked Potentials,P50 Wave,P600 Evoked Potentials,Potentials, Event-Related,Event Related Potentials,Event-Related Potential,Evoked Potential, N100,Evoked Potential, N200,Evoked Potential, N300,Evoked Potential, N400,Evoked Potential, P200,Evoked Potential, P50,Evoked Potential, P600,Evoked Potentials, N100,Evoked Potentials, N200,Evoked Potentials, N300,Evoked Potentials, N400,Evoked Potentials, P200,Evoked Potentials, P50,Evoked Potentials, P600,N1 Waves,N2 Waves,N200 Evoked Potential,N3 Waves,N300 Evoked Potential,N4 Waves,N400 Evoked Potential,P2 Waves,P200 Evoked Potential,P50 Waves,P600 Evoked Potential,Potential, Event Related,Potential, Event-Related,Potential, Evoked,Potentials, Event Related,Potentials, Evoked,Potentials, N400 Evoked,Related Potential, Event,Related Potentials, Event,Wave, N1,Wave, N2,Wave, N3,Wave, N4,Wave, P2,Wave, P50,Waves, N1,Waves, N2,Waves, N3,Waves, N4,Waves, P2,Waves, P50
D005583	Fourier Analysis	Analysis based on the mathematical function first formulated by Jean-Baptiste-Joseph Fourier in 1807. The function, known as the Fourier transform, describes the sinusoidal pattern of any fluctuating pattern in the physical world in terms of its amplitude and its phase. It has broad applications in biomedicine, e.g., analysis of the x-ray crystallography data pivotal in identifying the double helical nature of DNA and in analysis of other molecules, including viruses, and the modified back-projection algorithm universally used in computerized tomography imaging, etc. (From Segen, The Dictionary of Modern Medicine, 1992)	Fourier Series,Fourier Transform,Analysis, Cyclic,Analysis, Fourier,Cyclic Analysis,Analyses, Cyclic,Cyclic Analyses,Series, Fourier,Transform, Fourier
D006317	Hearing Loss, Noise-Induced	Hearing loss due to exposure to explosive loud noise or chronic exposure to sound level greater than 85 dB. The hearing loss is often in the frequency range 4000-6000 hertz.	Acoustic Trauma,Hearing Loss, Noise Induced,Noise-Induced Hearing Loss
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328	Adult	A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available.	Adults
D012815	Signal Processing, Computer-Assisted	Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.	Digital Signal Processing,Signal Interpretation, Computer-Assisted,Signal Processing, Digital,Computer-Assisted Signal Interpretation,Computer-Assisted Signal Interpretations,Computer-Assisted Signal Processing,Interpretation, Computer-Assisted Signal,Interpretations, Computer-Assisted Signal,Signal Interpretation, Computer Assisted,Signal Interpretations, Computer-Assisted,Signal Processing, Computer Assisted
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model