Abstract: A method and apparatus for sound enhancement are provided in this invention. The method comprises: obtaining sound signals and converting the sound signals into digital signals; decomposing the digital signals to obtain a plurality of IMFs or pseudo-IMFs; selectively amplifying the amplitudes of the IMFs and pseudo-IMFs; reconstituting the selectively amplified IMFs or pseudo-IMFs to obtain reconstituted signals and converting the reconstituted signals into analog signals. The present invention is based on the Hilbert-Huang transform. Through the present invention, the sound can be selectively amplified, and only the high-frequency consonants in the sound are amplified without vowel, which effectively improves the clarity of the enhanced sound. The present invention overcomes the problems in the current sound enhancement method which makes the sound louder without increasing the clarity.

Abstract: The present invention provides a construction method for automatic sleep staging and use thereof.

Abstract: The invention discloses a speech processing method and system in a cochlear implant. The method includes: obtaining a sound signal, and converting the sound signal into a digital signal; decomposing the digital signal using a mode decomposition method, obtaining a plurality of intrinsic mode functions, and converting the plurality of intrinsic mode functions into instantaneous frequencies and instantaneous amplitudes or instantaneous energy intensities; sorting the instantaneous frequencies to corresponding the preset electrode frequency bands of the electrodes in the cochlear implant; selecting N most energetic components from the corresponding frequency bands of the electrodes, and generating corresponding electrode stimulation signals according to the selected components. The present invention analyzes sound and composes the final electrode signals all in the time domain based on Hilbert-Huang transform; it is not limited by the principle of uncertainty, and there is no noise generated by harmonics.

Abstract: A method and apparatus for sound enhancement are provided in this invention. The method comprises: obtaining sound signals and converting the sound signals into digital signals; decomposing the digital signals to obtain a plurality of IMFs or pseudo-IMFs; selectively amplifying the amplitudes of the IMFs and pseudo-IMFs; reconstituting the selectively amplified IMFs or pseudo-IMFs to obtain reconstituted signals and converting the reconstituted signals into analog signals. The present invention is based on the Hilbert-Huang transform. Through the present invention, the sound can be selectively amplified, and only the high-frequency consonants in the sound are amplified without vowel, which effectively improves the clarity of the enhanced sound. The present invention overcomes the problems in the current sound enhancement method which makes the sound louder without increasing the clarity.

Abstract: A noninvasive arterial condition detecting system includes a processing device and an electronic stethoscope configured for auscultating carotid artery to receive sound signals. The processing device is connected to the electronic stethoscope. The processing device records the sound signals, preprocesses the sound signal to reduce noise, measures a trough-peak distance and a trough-peak time, and generates an estimate result of arterial conditions according to the trough-peak distance and the trough-peak time. The trough-peak distance and the trough-peak time are related to the health of the carotid artery walls.

Abstract: A noninvasive arterial condition detecting system includes a processing device and an electronic stethoscope configured for auscultating carotid artery to receive sound signals. The processing device is connected to the electronic stethoscope. The processing device records the sound signals, preprocesses the sound signal to reduce noise, measures a trough-peak distance and a trough-peak time, and generates an estimate result of arterial conditions according to the trough-peak distance and the trough-peak time. The trough-peak distance and the trough-peak time are related to the health of the carotid artery walls.

Abstract: An analysis module is provided in the invention. The analysis module is connected with a database containing several data. The analysis module comprises an analysis unit and a database managing system. The analysis unit is developed by a development software to combine HHT algorithm and an automatic data-loading program. The database managing system is integrated in the analysis unit and connected with the database. The data are transferred to the analysis unit by the database managing system, and the analysis unit is used to load the data by the automatic data-loading program and analyzes the data.

Abstract: The present invention provides a cell phone and a case, wherein the case includes a external system and a internal system, wherein the external system includes a signal receive part, a cell phone case, a connector and a defibrillator part, wherein the internal portion includes an power supply part, a amplifying part and a signal processing part; the present invention also provides a method for removal of cardiac ventricular fibrillation.

Abstract: A degree of nonlinearity based on intra-wave frequency modulation is proposed here with the value substantially between 0 and 1. The degree of nonlinearity is used for obtaining the state rather than a system. The data required for defining the degree of nonlinearity is the state of the motion or the observed data. For a complicate state with more than one IMF containing prominent energy density, the degree of nonlinearity has also considered the amplitude variations. The combination of the intra-wave frequency modulation and the amplitude variation gives the Combined Degree of nonlinearity. With the definitions of degree of nonlinearity, the nonlinearity characteristic can be quantified, and the discussion of nonlinear effects could be conducted more precisely.

Abstract: An analysis module is provided in the invention. The analysis module is connected with a database containing several data. The analysis module comprises an analysis unit and a database managing system. The analysis unit is developed by a development software to combine HHT algorithm and an automatic data-loading program. The database managing system is integrated in the analysis unit and connected with the database. The data are transferred to the analysis unit by the database managing system, and the analysis unit is used to load the data by the automatic data-loading program and analyzes the data.

Abstract: A degree of nonlinearity based on intra-wave frequency modulation is proposed here with the value substantially between 0 and 1. The degree of nonlinearity is used for obtaining the state rather than a system. The data required for defining the degree of nonlinearity is the state of the motion or the observed data. For a complicate state with more than one IMF containing prominent energy density, the degree of nonlinearity has also considered the amplitude variations. The combination of the intra-wave frequency modulation and the amplitude variation gives the Combined Degree of nonlinearity. With the definitions of degree of nonlinearity, the nonlinearity characteristic can be quantified, and the discussion of nonlinear effects could be conducted more precisely.

Abstract: A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's.