The technique utilizes the Doppler effect of frequency shift as the sound is reflected from moving objects. In medical imaging, Doppler ultrasound is used to quantify blood flow. In medicine, similar applications are far less plentiful, although automatic analysis of respiratory, heart and bowel sounds have been explored 4, 5, 6. Fingerprinting has been applied to audio signals in speech recognition software, in music and environmental sound identification, allowing search and retrieval of identical or similar audio signals from databases 1, 2, 3. Thus the presence of an exact match or the degree of similarity can be determined by a search. Search in this context refers to either finding an exact match to a given sound, or finding sounds that have similar features. The purpose of audio fingerprinting is to construct a quantitative, digital summary of an audio signal, which can then be used for matching and searching among large numbers of signals 1. Audio fingerprinting of medical Doppler signals is potentially useful for indexing and search for similar and dissimilar audio samples in a dataset.Īudio fingerprinting is inspired by the human fingerprint, which functions as a small but unique representation of a person. The results indicate that the proposed frequency based classification has a perceptual relevance for human listeners and that the method is feasible. These findings were significantly different from the score expected by chance (p < 0.001). The panel of listeners had an 88% agreement with the classification based on quantitative frequency features. The ranking of sound files according to degree of similarity differed between the frequency and conventional classification methods.
These pairings were compared to a similar classification based on standard quantitative parameters used in medical ultrasound and to classification performed by a panel of listeners. From this 10 audio samples were pairwise classified as being either similar or dissimilar. Frequency features were extracted from each periodogram and included in a principal component analysis (PCA). Power Doppler periodograms were generated from 84 ultrasonographic Doppler signals from the common carotid arteries in 22 dogs.
We propose a similar approach with medical ultrasonographic Doppler audio signals. Audio fingerprinting involves extraction of quantitative frequency descriptors that can be used for indexing, search and retrieval of audio signals in sound recognition software.
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