On the speech envelope in the cortical tracking of speech.

The synchronization between the speech envelope and neural activity in auditory regions, referred to as cortical tracking of speech (CTS), plays a key role in speech processing. The method selected for extracting the envelope is a crucial step in CTS measurement, and the absence of a consensus on best practices among the various methods can influence analysis outcomes and interpretation. Here, we systematically compare five standard envelope extraction methods the absolute value of Hilbert transform (absHilbert), gammatone filterbanks, heuristic approach, Bark scale, and vocalic energy), analyzing their impact on the CTS. We present performance metrics for each method based on the recording of brain activity from participants listening to speech in clear and noisy conditions, utilizing intracranial EEG, MEG and EEG data. As expected, we observed significant CTS in temporal brain regions below 10 Hz across all datasets, regardless of the extraction methods. In general, the gammatone filterbanks approach consistently demonstrated superior performance compared to other methods. Results from our study can guide scientists in the field to make informed decisions about the optimal analysis to extract the CTS, contributing to advancing the understanding of the neuronal mechanisms implicated in CTS.

Envelope Extraction for Vibration Locating in Coherent Φ-OTDR.

In a coherent phase-sensitive optical time-domain reflectometry (Φ-OTDR) sensing system, a frequency shift of hundreds of MHz generated by the pulse modulation of an acoustic optic modulator results in a high central frequency of a beating signal spectrum. In order to reduce the high-performance hardware requirement of signal acquisition, the coherent Φ-OTDR based on envelope extraction is proposed in this paper. Firstly, a theoretical model of a quasi-sinusoidal amplitude-modulated signal is built for the beating signal between local oscillator light and Rayleigh backward scattering light. An envelope detector is then utilized to realize the envelope extraction of beating signals with advantages of a simple structure and quick response. The extracted envelope can be directly used for vibration locating without the conventional orthogonal demodulation. Experiment results present that the sampling rate can be reduced to 10 MHz under the spatial resolution of 10 m and the sensing distance of 31 km. This scheme proves that envelope extraction is a reliable technical route for vibration locating, which can effectively reduce the sampling rate and simplify the data demodulation.

Multistage decision-based heart sound delineation method for automated analysis of heart sounds and murmurs.

A robust multistage decision-based heart sound delineation (MDHSD) method is presented for automatically determining the boundaries and peaks of heart sounds (S1, S2, S3, and S4), systolic, and diastolic murmurs (early, mid, and late) and high-pitched sounds (HPSs) of the phonocardiogram (PCG) signal. The proposed MDHSD method consists of the Gaussian kernels based signal decomposition (GSDs) and multistage decision-based delineation (MDBD). The GSD algorithm first removes the low-frequency (LF) artefacts and then decomposes the filtered signal into two subsignals: the LF sound part (S1, S2, S3, and S4) and the high-frequency sound part (murmurs and HPSs). The MDBD algorithm consists of absolute envelope extraction, adaptive thresholding, and fiducial point determination. The accuracy and robustness of the proposed method is evaluated using various types of normal and pathological PCG signals. Results show that the method achieves an average sensitivity of 98.22%, positive predictivity of 97.46%, and overall accuracy of 95.78%. The method yields maximum average delineation errors of 4.52 and 4.14 ms for determining the start-point and end-point of sounds. The proposed multistage delineation algorithm is capable of improving the delineation accuracy under time-varying amplitudes of heart sounds and various types of murmurs. The proposed method has significant potential applications in heart sounds and murmurs classification systems.

A Novel Method for Extraction of Heart Sounds Envelope Based on Interpolation of Local Peak and Valley Points / 航天医学与医学工程

Objective To extract envelope of heart sounds exactly,for the purpose of the further analysis of its characteristics.Methods The way that envelope extraction of heart sounds based on key-points was given.The points of local peak and valley were calculated firstly,and then heart sound envelope was gotten by the interpolation of these points.Results Compared with the envelope extracted by Hilbert-transform and mathematical morphology,respectively,the outline of heart sounds was extracted more accurately,and its time-domain characters were acquired by this method.Conclusion The envelope of heart sound is extracted correctly by this method,which is useful for the further analysis.

Envelope Extraction of Heart Sounds Based on Hilbert-Huang Transform / 航天医学与医学工程

Objective Based on the analysis of time domain of heart sound with envelop to extract the envelope character of heart sounds.Methods The envelope extraction of heart sounds based on Hilbert-Huang Transform was given.Firstly,the original heart sounds signal was preprocessed by Huang Transform.Secondly,the envelope of heart sounds was got with Hilbert Transform.Results The first heart sound and the second heart sound were extracted,and all kinds of characters in time domain of heart sound were acquired more accurately.Conclusion The envelope of heart sound is extracted correctly.The foundation for further analysis of heart sounds is established.