National Central University

Other

Dynadx Corporation

National Yang Ming Chiao Tung University

Chi-hua Foundation

Men-Tzung Lo

Chen Lin

Yi-Chung Chang

Norden E Huang

Shih-Ann Chen

Wan-Hsin Hsieh

Hsiang-Chih Chang

Yenn-Jiang Lin

Matthew Huei-Ming Ma

Kun Hu

Lian-Yu Lin

Yu-Cheng Lin

Bo-Jau Kuo

Pa-Chun Wang

Yanhui Liu

Thi-Thao Tran

Yung-Hung Wang

Van-Truong Pham

Patrick Chow-In Ko

Chung-Kang Peng

Hui-Wen Yang

Xian-Yao Chen

Te-Yung Fang

Zhao-Hua Wu

Ting-Fang Shih

Wan-Lin Wu

Fa-Po Chung

Leh-Kiong Huon

Hsu-Wen Vincent Young

Cheng-Yen Wang

Han-Hwa Hu

Wen-Chu Chiang

Ke-Hsin Hsu

Yunn-Jy Chen

Huan-Yu Kuo

Hung-Yi Lee

A multi-channel real-time cardiovascular performance evaluation system, includes: a multi-channel ECG signals measurement unit, a multi-channel ECG signals processing device, and an ECG signals reconstruction unit. The method uses a MAMA-END algorithm, to mark ECG signals to replace the original ECG signal, and to extract characteristic peak value of the ECG signal. As such, the method is able to extract and reconstruct a first signal having QRS wave, and a second signal having T wave; then the method detects and marks the start of Q wave and the end of T wave on the first signal and the second signal. Therefore, the method is able to determine and evaluate if a patient does have cardiovascular disease, and to locate the lesion positions of a patient having cardiovascular disease.

Multi-channel real-time cardiovascular performance evaluation system and method cardiovascular performance evaluation system and method

The present invention provides a bed set for inhibition of obstructive sleep apnea, which includes: a sound receiving module, is used to receive a respiratory sound signal obtained from a user during a time period; a sound analyzing processor, which is connected with the sound receiving module, is used to obtain a snoring sound characteristic from the spectrum of respiratory sound signal; a database, which has a plurality of snoring image characteristics corresponding to a plurality of basic snoring sound characteristics for different respiratory actions; a control processor, which is connected with the sound analyzing processor and the database, is used to compare the snoring sound characteristic with the basic snoring sound characteristics to select one of the snoring image characteristics in the same waveform, and provides the first angle control order and the second angle control order corresponding to the selecting snoring image characteristic; a first pillow, which is connected to the control processor, declines a first angle toward a declination direction after receiving the first control order; and a second pillow, which is connected to the control processor, declines a second angle toward the declination direction after receiving the second control order.

Bed set for inhibition obstructive sleep apnea

The present invention provides a diagram building system adapted for processing a signal with a time period. The diagram building system comprises a inputting device for receiving the signal; a computing device, dividing the signal into a plurality of window scales according to one of time interval scales; decomposing the window scales via HHT algorithm to generate a plurality of quantized windows according to different components; then, calculating the value of quantized windows with the same single-frequency component through a quantifying function to generate a plurality of specific frequency values; an outputting device, sequentially arranging the specific frequency values according to the time interval scales and the single-frequency components to form a visual diagram.

Diagram building system and method for a signal data decomposition and analysis

The invention provides a system and a method for an otitis media database constructing. The steps of method comprise: First, receiving a plurality of tympanic membrane images, wherein the tympanic membrane images are ear infection in different types. Second, choosing one of the tympanic membrane images, then classifying into a plurality of anatomic regions based on a plurality of tissue types. Coding each of anatomic regions with a numerical number to describe its morbid condition, and obtaining an eigenvalue through collecting the numerical number of each anatomic region. Furthermore, repeatedly choosing other one of tympanic membrane images until each tympanic membrane image obtaining the eigenvalue. And obtaining a matrix through collecting the eigenvalue of each tympanic membrane image, then generating an otitis media database.

System and method for an otitis media database constructing and an image analyzing

A method implemented through an electronic system for processing a sequential data to identify possible peak points is disclosed. The method defines a decayed threshold function and partition the sequential data into a plurality of segments by grouping each data point with surrounding data points into one of the segments. After that, a plurality of weighted segments are derived through weighting the surrounding data points by the decayed threshold function in each of the segments, and the peak points are identified through corresponding weighted segment.

Methods for processing sequential data to identify possible peak points and to estimate peak to noise ratio of sequential data

A computer-assisted method for quantitatively characterizing atrial fibrillation in a patient includes recording time series of bipolar atrial fibrillation signals at multiple sites in a patient's atria using two or more electrodes, calculating a similarity index vector by a computer system based on the bipolar atrial fibrillation signal between a first site and its neighboring sites, constructing an similarity-index vector field based on similarity-index vectors at different sites, calculating Curl and Divergence of the similarity-index vector field, calculating Rotor Identification using Curl and Divergence, calculating Focal Identification using Divergence, and determining one or more critical regions in the patient's atria if Rotor Identification is above a first predetermined threshold and Focal Identification is above a second predetermined threshold.

Accurately indetifying critcal regions in atrial fibrillation by identifying rotors in directional similarity vector field

This invention discloses a system and a method for extracting VF signal in ECG recorded during uninterrupted CPR. The present invention provides a method for extracting a Ventricular fibrillation (VF) signal in Electrocardiography (ECG), comprising: receiving an ECG signal; adding a plurality of shadowing functions to the ECG signal, to obtain a plurality of modification signals; decomposing the plurality of modification signals by using an Empirical Mode Decomposition (EMD) method, to generate a plurality of Intrinsic Mode Functions (IMFs); calculating the sum of IMFs in different frequency regions based on time sequence, dividing by a number of the shadowing signal, to obtain a plurality of modification intrinsic mode functions; combining the plurality of modification IMFs with the same property, to obtain a shape function; modeling the shape functions to obtain a compression signal; and subtracting the compression signal from the ECG signal based on time sequence, to obtain the VF signal.

Method and system for extracting ventricular fibrillation signals in electrocardiogram using spline interpolation with uniform phase ensembles

A computer-assisted method for quantitative characterizing atrial fibrillation (AF) in a patient includes recording unipolar atrial fibrillation signals from multiple sites in a patient's atria, calculating bipolar electrograms using unipolar AF signals recorded at adjacent sites by a computer system, applying Empirical Mode Decomposition to remove a background from the bipolar electrogram signal to obtain a filtered bipolar electrogram signal, applying Hilbert transform to an envelope function of the filtered bipolar electrogram signal to obtain a time series of instantaneous phases of the filtered bipolar electrogram signal, and identifying a rotor region in patient's atria using the instantaneous phases in the filtered bipolar electrogram signal.

System and method for indentifying rotors in fractionated signals in persistent atrial fibrillation ablation

A computer-assisted method for quantitative analysis of respiratory sinus arrhythmia (RSA) includes obtaining a time series of a cardiac interval signal from an individual, obtaining a time series of a respiratory signal from the individual; decomposing the cardiac interval signal into a first group of ensemble empirical modes; obtaining, by a computer system, a time series of RSA instantaneous amplitude from at least one of the first group of ensemble empirical modes; decomposing the respiratory signal into a second group of ensemble empirical modes; obtaining a time series of respiratory instantaneous phase from the one of the second group of ensemble empirical modes; determining respiratory period from the time series of the respiratory instantaneous phase; and quantifying RSA in the individual according to a dependence of the RSA instantaneous amplitude on the respiratory period.

System and method for quantitative analysis of respiratory sinus arrhythmia

This invention discloses a system and method for extracting VF signal in ECG recorded during uninterrupted CPR. The method and system applies an adaptive algorithm incorporating the EMD and least mean square (LMS) filtering to effectively model the CPR artifacts such as chest compression signals. Thus, A VF signal in ECG recorded during uninterrupted CPR can be extracted without deteriorating the reliability of the waveform parameter (i.e. AMSA) of shockability. The present invention enables uninterrupted CPR performed during recording ECG for accessing the shockability, so that an increase the probability of successful resuscitation is achieved.

Method and system for extracting ventricular fibrillation signals in electrocardiogram

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.

Analysis module, cloud analysis system and method thereof

A computer-assisted method for quantitative characterization and treatment of ventricular fibrillation includes preprocessing a time series of an atrial fibrillation signal obtained from a patient, segmenting the time series of the AF signal into activation segments by the computer system, obtaining local activation waveforms (LAW) from the activation segments, determining degrees of similarity between the LAWs, and identifying one or more critical regions in the patient's atria if the LAWs have degrees of similarity exceeding a first threshold value.

System and method for improved complex fractionated electrogram ablation

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.

Method for quantifying and modeling degree of nonlinearity, combined nonlinearity, and nonstationarity

A computer-assisted method for quantitative characterization and treatment of ventricular fibrillation includes acquiring a time series of a ventricular fibrillation (VF) signal using a probe from a patient experiencing VF, subtracting the mean from the time series of the VF signal, calculating a cumulative VF signal after the mean is subtracted from the time series of the VF signal, segmenting the cumulative VF signal by a plurality of sampling boxes, calculating the root-mean-square of the cumulative VF signal as a function of the sampling box size , extracting an exponent of the root-mean-square of the cumulative VF signal as a function of the sampling box size, applying electrical defibrillation to the patient if the exponent is below a predetermined value, and applying cardiopulmonary resuscitation (CPR) to the patient if the exponent is above a predetermined value.

System and method for predicting successful defibrillation for ventricular fibrillation cardiac arrest

A method for dynamic cerebral autoregulation (CA) assessment includes acquiring a blood pressure (BP) signal having a first oscillatory pattern from a first individual, acquiring a blood flow velocity (BFV) signal having a second oscillatory pattern from the first individual, decomposing the BP signal into a first group of intrinsic mode functions (IMFs), decomposing the BFV signal into a second group of IMFs, determining dominant oscillatory frequencies in the first group of IMFs, automatically selecting a first characteristic IMF from the first group of IMFs that has its associated dominant oscillatory frequency in a predetermined frequency range, automatically selecting a second characteristic IMF from the second group of IMFs, calculating a time sequence of instantaneous phase difference between the first characteristic IMF and the second characteristic IMF, computing an average of the instantaneous phase difference in the time sequence, and identifying a pathological condition in the first individual.

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Jhongli, Taiwan

Men-Tzung Lo