Abstract: Processing of plethysmographic signals via the cepstral domain is provided. In one embodiment, a cepstral domain plethysmographic signal processing method (200) includes the steps of obtaining (210) time domain plethysmographic signals, smoothing (220) the time domain plethysmographic signals, performing (230) a first-stage Fourier transformation of the time domain plethysmographic signals to frequency domain plethysmographic signals, computing (240) power spectrums from the frequency domain plethysmographic signals, scaling (250) the power spectrums with a logarithmic function, performing (260) a second-stage Fourier transformation on log-scaled spectrums to transform the power spectrums into cepstrums, and examining (270) the cepstrums to obtain information therefrom relating to a physiological condition of the patient such as the patient's pulse rate or SPO2 level.

Abstract: Pulse oximetry is improved through classification of plethysmographic signals by processing the plethysmographic signals using a neural network that receives input coefficients from multiple signal domains including, for example, spectral, bispectral, cepstral and Wavelet filtered signal domains. In one embodiment, a plethysmographic signal obtained from a patient is transformed (240) from a first domain to a plurality of different signal domains (242, 243, 244, 245) to obtain a corresponding plurality of transformed plethysmographic signals. A plurality of sets of coefficients derived from the transformed plethysmographic signals are selected and directed to an input layer (251) of a neural network (250). The plethysmographic signal is classified by an output layer (253) of the neural network (250) that is connected to the input layer (251) by one or more hidden layers (252).

Abstract: Processing of plethysmographic signals via the cepstral domain is provided. In one embodiment, a cepstral domain plethysmographic signal processing method (200) includes the steps of obtaining (210) time domain plethysmographic signals, smoothing (220) the time domain plethysmographic signals, performing (230) a first-stage Fourier transformation of the time domain plethysmographic signals to frequency domain plethysmographic signals, computing (240) power spectrums from the frequency domain plethysmographic signals, scaling (250) the power spectrums with a logarithmic function, performing (260) a second-stage Fourier transformation on log-scaled spectrums to transform the power spectrums into cepstrums, and examining (270) the cepstrums to obtain information therefrom relating to a physiological condition of the patient such as the patient's pulse rate or SPO2 level.

Abstract: Processing of plethysmographic signals via the cepstral domain is provided. In one embodiment, a cepstral domain plethysmographic signal processing method (200) includes the steps of obtaining (210) time domain plethysmographic signals, smoothing (220) the time domain plethysmographic signals, performing (230) a first-stage Fourier transformation of the time domain plethysmographic signals to frequency domain plethysmographic signals, computing (240) power spectrums from the frequency domain plethysmographic signals, scaling (250) the power spectrums and performing (260) a second-stage Fourier transformation on the log-scaled spectrums to transform the power spectrums into cepstrums, and examining (270) the cepstrums to obtain information therefrom relating to a physiological condition of the patient such as the patient's pulse rate or SPO2 level.

Abstract: Processing of plethysmographic signals via the cepstral domain is provided. In one embodiment, a cepstral domain plethysmographic signal processing method (200) includes the steps of obtaining (210) time domain plethysmographic signals, smoothing (220) the time domain plethysmographic signals, performing (230) a first-stage Fourier transformation of the time domain plethysmographic signals to frequency domain plethysmographic signals, computing (240) power spectrums from the frequency domain plethysmographic signals, scaling (250) the power spectrums with a logarithmic function, performing (260) a second-stage Fourier transformation on log-scaled spectrums to transform the power spectrums into cepstrums, and examining (270) the cepstrums to obtain information therefrom relating to a physiological condition of the patient such as the patient's pulse rate or SPO2 level.

Abstract: Processing of plethysmographic signals via the cepstral domain is provided. In one embodiment, a cepstral domain plethysmographic signal processing method (200) includes the steps of obtaining (210) time domain plethysmographic signals, smoothing (220) the time domain plethysmographic signals, performing (230) a first-stage Fourier transformation of the time domain plethysmographic signals to frequency domain plethysmographic signals, computing (240) power spectrums from the frequency domain plethysmographic signals, scaling (250) the power spectrums with a logarithmic function, performing (260) a second-stage Fourier transformation on log-scaled spectrums to transform the power spectrums into cepstrums, and examining (270) the cepstrums to obtain information therefrom relating to a physiological condition of the patient such as the patient's pulse rate or SPO2 level.

Abstract: A computer-based method and apparatus for classifying statement types using intonation analysis. The method and apparatus identify a user's potential query when the user responds to information during dialog with an automated dialog system. Pitch information is extracted, via a cepstrum, from the speech signal. In one embodiment, the pitch intonation is processed to form a smoothed pitch or intonation contour. Then the smoothed pitch contour is processed by a set of shape detectors and this output, together with statistical information, is sent to a rule-based algorithm which attempts to classify the statement type. In another embodiment, the smoothed pitch contour is processed by a pattern recognition system such as a neural network trained with a back-propagation learning algorithm.

Abstract: A method and apparatus for enhancing the intelligibility of a telephonic speech signal within the available bandwidth and intensity limits of a telephone communication network. The method combines enhancement of both the formant ratio and the consonant/vowel energy ratio to realize a speech signal more intelligible to a hearing impaired user. The invention uses an auditory model of the human ear. A speech signal is put through a filter bank designed to simulate the cochlear filter shapes and filter spacing of a healthy cochlea. The energy output from each of a plurality of filters is computed and used to form an auditory spectrum. The peaks associated with strong first and second formants are identified, and the second formant is enhanced relative to the first formant by attenuating the first formant. Also, consonants in the speech signal are identified as having an energy level below a threshold associated with vowels, but above the threshold associated with silent regions. Consonant regions are amplified.