Diffuse Terahertz Spectroscopy in Turbid Media Using a Wavelet-Based Bimodality Spectral Analysis

Current terahertz (THz) spectroscopy techniques only use the coherent light beam for spectral imaging. In the presence of electromagnetic scattering, however, the scattering-mitigated incoherent beams allow for flexible emitter-detector geometries, which enable applications such as seeing through turbid media. Despite this potential, THz spectroscopy using diffuse waves has not been demonstrated. The main obstacles are the very poor signal to noise ratios of the diffused fields and the resonance-like spectral artifacts due to multiple Mie scattering events that obscure the material absorption signatures. In this work, we demonstrate diffuse THz spectroscopy of a heterogeneous sample through turbid media using a novel technique based on the wavelet multiresolution analysis and the bimodality coefficient spectrum, which we define here for the first time using the skewness and kurtosis of the spectral images. The proposed method yields broadband and simultaneous material characterization at detection angles as high as 90o with respect to the incident beam. We determined the accuracy of the wavelet-based diffuse spectroscopy at oblique detection angles, by evaluating the area under the Receiver Operating Characteristic (ROC) curves, to be higher than 95%. This technique is agnostic to any a priori information on the spectral signatures of the sample materials or the characteristics of the scattering medium, and can be expanded for other broadband spectroscopic modalities.

Diffuse terahertz spectroscopy in turbid media using a wavelet-based bimodality spectral analysis

Current terahertz (THz) spectroscopy techniques only use the coherent light beam for spectral imaging. In the presence of electromagnetic scattering, however, the scattering-mitigated incoherent beams allow for flexible emitter-detector geometries, which enable applications such as seeing through turbid media. Despite this potential, THz spectroscopy using diffuse waves has not been demonstrated. The main obstacles are the very poor signal to noise ratios of the diffused fields and the resonance-like spectral artifacts due to multiple Mie scattering events that obscure the material absorption signatures. In this work, we demonstrate diffuse THz spectroscopy of a heterogeneous sample through turbid media using a novel technique based on the wavelet multiresolution analysis and the bimodality coefficient spectrum, which we define here for the first time using the skewness and kurtosis of the spectral images. The proposed method yields broadband and simultaneous material characterization at detection angles as high as 90° with respect to the incident beam. We determined the accuracy of the wavelet-based diffuse spectroscopy at oblique detection angles, by evaluating the area under the receiver operating characteristic curves, to be higher than 95%. This technique is agnostic to any a priori information on the spectral signatures of the sample materials or the characteristics of the scattering medium, and can be expanded for other broadband spectroscopic modalities.

Method for detecting R-waves of an ECG signal based on wavelet decomposition

Increasing the efficiency of cardiological diagnostics based on the analysis of human heart rate variability necessitates the development of accurate methods for detecting the R-waves of the electrocardiosignal (ECG signal). A technique for detecting R-waves of an ECG signal based on the wavelet multiresolution analysis (WMRA). The proposed technique for detecting R-waves includes sequential stages of digital processing of an ECG signal: WMRA; a set of nonlinear operators; adaptive algorithm for detecting signal peaks. A comparative analysis of the proposed technique with existing approaches to the detection of R-waves of the ECG signal has been carried out. To obtain quantitative characteristics of evaluating the efficiency of detecting R-waves, we used imitation modeling of an ECG signal containing noises and interferences of various intensity and nature of occurrence. The effectiveness of the considered approaches to the detection of R-waves of the ECG signal was investigated for clinical recordings of ECG signal. The absolute error of measuring the RR-interval durations for model signals with different noise levels is estimated. It is shown that the proposed method for detecting R-waves of an ECG signal based on WMRA is characterized by small errors in measuring the duration of RR-intervals, high rates of true detection and small errors of false detection and omission.