374 results about "Waveform analysis" patented technology

The invention relates to methods and devices for measuring pulsus paradoxus. The methods herein employ a combination of one or more forms of waveform analysis for the purpose of measuring pulsus paradoxus and diagnosing respiratory distress. The methods also combine measurements of pulsus paradoxus and physician assessments to diagnose respiratory distress. The methods also combine measurements of pulsus paradoxus and percentage oxygenated hemoglobin to diagnose respiratory distress. The devices of this invention employ pulse oximeters, arterial tonometers, finometers, or processors for the purpose of implementing the methods of the invention.

A capnograph which performs an analysis of the breath waveforms measured by the carbon dioxide sensor, interprets the results of this analysis, and outputs to the operator diagnostic information about the respiratory status of the patient, or about the adequacy of the breathing support provided to the patient. The instrument compares a number of parameters characteristic of the waveforms of the patient's breath with an internal library of the values of those parameters expected from normal waveforms stored in its memory. These parameters may either relate to specific features of the waveform in the time domain, or may characterize spectral components of the waveform in the frequency domain. The capnographic waveform analysis may be combined with further non-invasive measurements in order to provide an indication of the deviation of the value of EtCO₂ from PaCO₂.

The invention relates to a physiological signal quality evaluation method and system based on constrained estimation. The method comprises the following steps: receiving to-be-evaluated signal sections of a quasi-periodic physiological signal, performing pretreatment, waveform analysis identification and signal period segmentation to the signal sections, carrying out feature point detection to each cycle of signal section, and extracting preset physiological feature parameters of the physiological signal; for each signal section, combining the extracted physiological feature parameters to form feature vectors, performing constraint-based modeling according to transcendental knowledge of the physiological signal, and further establishing an analyzable evaluation system with constraint timing; and using a constraint evaluation model to trace sequential change of physiological parameters, combing a preset rule base and sequential change information, rating the signal quality of the quasi-periodic physiological signal, evaluating the validity of signal data of the signal sections of the quasi-periodic physiological signal, updating a time sequence evaluation system, and rating according to iteration of the periodic signal sections until the signal quality rating of all the signal sections of the quasi-periodic physiological signal is finished.

A user configurable variable mode pulse indicator provides a user the ability to influence outputs indicative of a pulse occurrence at least during distortion, or high-noise events. For example, when configured to provide or trigger pulse indication outputs, a pulse indicator designates the occurrence of each pulse in a pulse oximeter-derived photo-plethysmograph waveform, through waveform analysis or some statistical measure of the pulse rate, such as an averaged pulse rate. When the configured to block outputs or not trigger pulse indication outputs, a pulse indicator disables the output for one or more of an audio or visual pulse occurrence indication. The outputs can be used to initiate an audible tone “beep” or a visual pulse indication on a display, such as a vertical spike on a horizontal trace or a corresponding indication on a bar display. The amplitude output is used to indicate data integrity and corresponding confidence in the computed values of saturation and pulse rate. The amplitude output can vary a characteristic of the pulse indicator, such as beep volume or frequency or the height of the visual display spike.

The embodiment of the invention provides a seismic waveform analysis and reservoir prediction method and device; the method comprises the following steps that: a target reservoir is selected; the size of a window when in seismic waveform classification is selected; a plurality of model traces are created according to the number of categories of seismic facies; different waveforms are classified according to a self-organizing neural network; seismic facies classification parameters are processed to generate a seismic facies classification diagram; sedimentary facies identification signs are established to classify the sedimentary facies of a single well, the sedimentary facies of the single well are compared to generate the sedimentary facies of a well tie, so that the sedimentary facies between the wells are determined; the seismic facies at a well point are converted into sedimentary facies by integrating the sedimentary facies of the single well and the seismic facies; external pushing is carried out towards an area which is not drilled according to the seismic waveform type of the calibrated well point; geological interpretation is carried out to the whole seismic facies diagram by integrating the sedimentary facies of the well tie, and a sedimentary facies diagram is formed from point to surface; and reservoir prediction is carried out according to the sedimentary facies diagram. According to the method, research and reservoir prediction for a sedimentary facies belt can be facilitated, so that the working efficiency of exploration is improved.

The invention discloses a non-invasive multipath pulse wave detection device, which comprises at least two sensors, each of the sensors is provided with a fixing device thereon and connected to a signal processing unit, and the signals detected by the sensors are processed and stored by the signal processing unit. The invention synchronously collects pulse waves and wave velocities in a multipathmanner and uses a wave form processing technique for the pulse wave collecting points of the different sites of a human body, is capable of analyzing the wave velocities and the wave forms aiming at the different sites of the human body, and provides more specific information reflecting cardiovascular system states for clinic real-time monitor.

The invention discloses a heartbeat type classification method and device, and electrocardiogram equipment and belongs to the field of medical apparatuses. The method comprises steps that heartbeat waveform characteristic parameters are extracted from ECG signals, heartbeat and template heartbeat matching degree characteristic parameters are further extracted, analysis is carried out through a decision tree classifier, and the heartbeat type analysis result can be acquired through measurement. An extracted characteristic vector can be better present difference of the ECG signals, and disadvantages of utilizing only a waveform analytical method or a template analysis method are avoided. The invention further comprises the electrocardiogram equipment comprising the method. The method is advantaged in that the characteristic vector extraction algorithm is simple and easy for realization, the operation speed is fast, classification accuracy is high, and the method is suitable for a wearable electrocardiogram real-time monitoring automatic analysis diagnosis system.

The systems and methods of the present disclosure detect arcing patterns or impedance changes and adjust the level of electrosurgical energy provided to tissue based on the detected arcing patterns or impedance changes. In embodiments, the drag force imposed on the electrode or blade of an electrosurgical instrument may be controlled by adjusting the level of electrosurgical energy based on the detected arcing patterns or impedance changes. The arcing patterns or impedance changes may be detected by sensing voltage and/or current waveforms of the electrosurgical energy and analyzing the sensed voltage and/or current waveforms. The current and/or voltage waveform analysis may involve calculating impedance based on the sensed voltage and current waveforms and calculating changes in impedance over time. The waveform analysis may involve detecting harmonic distortion using FFTs, DFTs, Goertzel filters, polyphase demodulation techniques, and/or bandpass filters. The waveform analysis may involve determining a normalized difference or the average phase difference between the voltage and current waveforms.

A method of determining a state of ventricular fibrillation from a waveform, includes: performing calculations on the Fourier transform of the waveform voltage values by using the quotient of the power in a high frequency band and of the power in a low frequency band; and determining the state of ventricular fibrillation by relating this ratio to the state of ventricular fibrillation. A defibrillation system for use in treatment of ventricular fibrillation includes at least one sensor to measure heart rhythm and at least one applicator to apply a defibrillation shock to a patient. The system further includes at least one processor which is adapted to calculate the ratio and also to obtain user input regarding survival of subgroups and average response times in the user's domain which allows calculation of an estimated maximum overall survival and selection of an optimum threshold for the ratio measure based on this maximum. The system further includes a user interface system in operative connection with the processor to provide information related to the ratio to a user.

The invention discloses an electrocardiogram waveform classification method and device, and relates to the field of medical analysis software. The method comprises the following steps: acquiring and storing electrocardiogram data of a human body for 24 hours; performing waveform analysis on the electrocardiogram data to obtain electrocardiogram waveform corresponding to each heart beat in 24 hours; moving the electrocardiogram waveforms corresponding to the various heart beats to a preset longitudinal reference shaft, and superposing by taking the longitudinal reference shaft as a reference to form a cluster shape waveform; classifying the electrocardiogram waveforms according to the waveform shape of the cluster shape waveform to obtain different types of electrocardiogram waveforms. According to the method and the device, the electrocardiogram waveforms can be quickly and accurately classified.

Waveform analysis is performed to identify and characterize power-consuming devices operating on a building electrical circuit. Current waveforms are measured from the building circuit with electrical devices operating thereon. The waveforms are separated into wavelets and analyzed to identify a representative wavelet model which is transmitted to a server for analysis. The server compares the representative wavelet model to a predictive model built from waveform signatures of known electrical devices operating on a circuit. When the predictive model matches the representative wavelet model, the electrical devices contributing to the representative wavelet, their operating mode(s) (e.g., “on”, “off”, “paused”, “hibernating”) and/or their performance state(s) (e.g., normal operation, deterioration, or failure modes) can be identified. This information can be communicated as feedback to the consumer to facilitate more efficient and more cost-effective energy usage.

A system and method for automatically analyzing impedance and pH data from an esophageal probe includes a data collection system that collects and stores the output from the sensors for a certain period of time to locate reflux episodes in the waveforms. The data analysis system uses wavelet analysis to assist in locating bolus entry and exit points in the waveforms and to smooth waveforms for additional analysis.

The invention discloses a wrist watch type multi-parameter biosensor and relates to a self-adaptive detection method for physiological parameters and a multi-parameter intelligent monitoring wrist watch by the adoption of the method. The method comprises the steps that (1) human physiological parameter signals are collected; (2) the human physiological parameter signals are subjected to self-adaptive wavelet decomposition, and feature predictors and updaters are selected point by point in the decomposition process; (3) waveform analysis is conducted, interference signals in the decomposed signals are eliminated, and human physiological parameter signals without interference are obtained. The monitoring wrist watch comprises a base body, wherein the base body is provided with a central processing unit, a physiological parameter sensor used for collecting the human physiological parameter signals and various other sensors. The central processing unit processes data by the adoption of a self-adaptive wavelet decomposition method to obtain the human physiological parameter signals without interference. The wrist watch type multi-parameter biosensor effectively solves the problem of instability caused by large contact resistance generated when a daily wearing mode is adopted. The wrist watch type multi-parameter biosensor is convenient to use and can collect various human physiological signals, movement signals, environment signals and the like in real time.

A vascular sensing system includes blood flow restricting means, a sensor, and means for producing an output representing a return of blood flow after the blood vessel has been temporarily collapsed by the blood flow restricting means. The blood flow restricting means is capable of placement on a human toe having a blood vessel, and is capable of manipulating the blood vessel. The sensor is operably connected to the blood flow restricting means and is physically spaced from the toe. Further, a method of vascular sensing includes taking pressure measurements with an pressure cuff positioned on a toe, and conducting a waveform analysis of the pressure measurements to determine a return of blood flow pressure.

Aspects of the invention relates to systems and methods for hypovolemia and/or hypervolemia detection of a living subject using peripheral intravenous waveform analysis. In one embodiment, the method includes: acquiring, from a vein of the living subject, peripheral venous signals; performing a spectral analysis on the acquired peripheral venous signals to obtain a peripheral venous pressure frequency spectrum; and performing a statistical analysis on amplitudes of peaks of the peripheral venous pressure frequency spectrum to determine the blood volume status of the living subject in real time. Specifically, at least two peaks, respectively corresponding to a first frequency and a second frequency, are obtained on the peripheral venous pressure frequency spectrum. Amplitude change of the second peak is used to determine the blood volume status of the living subject. Hemorrhage may be detected when a significant amplitude decrease is detected from the second baseline peak to the second peak.

The invention discloses a method for verifying a polarity of a zero-sequence current transformer. A hardware part comprises a signal acquisition system; a software part comprises a waveform analysis system; and the method comprises the following steps of: capturing an instant single-phase earth fault signal which mainly includes a bus zero-sequence voltage and a zero-sequence current of each line through the signal acquisition system by utilizing the characteristic of frequent instant single-phase earth fault of a distribution network system; and identifying whether a polarity connecting wire of the zero-sequence current transformer of each line is correct through the waveform analysis system based on the maximum zero-sequence amplitude value of a fault line and the characteristic that the phase position is opposite to that of the zero-sequence current of a non-fault line. The method for verifying the polarity of the zero-sequence current transformer solves the polarity verification difficulty of the zero-sequence current transformer in a small-current grounding line selection system efficiently without adding any device or tool, is very time-saving, convenient and fast, and solves a big difficulty in the practical application of small-current products.

Method and system for motoring and obtaining information about quantity and characteristics of cementitious material In a rotating mixing drum. The present invention involves analysis of a sequence of values corresponding to a waveform reflecting the hydraulic pressure required to turn a concrete mixing drum at successive instances during rotation. Preferred embodiments involve the conversion of this time-domain data into the frequency-domain. Behavior of multiple harmonics can be examined in real time and further information obtained regarding physical properties of the concrete. Rheology or other properties can be adjusted by introducing a liquid into the concrete, based on a comparison between time-domain and/or frequency-domain values derived from a sample concrete in the drum and previously stored time-domain and/or frequency-domain values, which are preferably correlated with physical characteristics of concrete, such as slump, slump flow, load weight, and other factors.

According to some aspects, a waveform processor is provided for control of quantum mechanical systems. Some embodiments of the waveform processor may be used to control quantum systems used in quantumcomputation, such as qubits. According to some embodiments, a waveform processor may include a first sequencer configured to sequentially execute master instructions according to a defined order andoutput digital values in response to the executed master instructions, and a second sequencer coupled to the first sequencer and configured to generate analog waveforms at least in part by transforming digital waveforms according to digital values received from the first sequencer. The analog waveforms may be applied to a quantum system. In some embodiments, the waveform processor may further include a waveform analyzer configured to integrate analog waveforms received from a quantum system and output results of said integration to the first sequencer.

The invention provides a laser rangefinder correction method, the method comprises the steps: a plurality targets are arranged on a preset position with the same distance in sequence; wherein reflectivities corresponding to every targets are different; a laser rangefinder is utilized to receive a laser signal reflected by each target and performs waveform analysis on reflected laser signals, so that amplitude values and corresponding measuring distance values are obtained; fitting analyzing and processing are performed on all measuring distance values and amplitude values, and corresponding fitting function relations are obtained; the measuring distance values are corrected according to the fitting function relations, corrected distance values are obtained, according to the above steps, an amplitude-phase error because of different reflectivities is minimized, so that the precision of distance measurement is improved.

A repair device for measurement, sampling device and waveform analysis device, which can analyze the waveform which is sampled from an output signal of a sensor, is provided to restrict the power consumption of the repair device for measurement. A repair device for measurement comprises an acceleration sensor(44) and a control member. The acceleration sensor outputs the acceleration value showing the acceleration. The control member controls two measurement states and operation states. The control member has the first control member and the second control member. The first control member reiterates acceleration value capturing, a fixed captured value, and the relation of threshold value for a fixed time. The second control member determines that the walk of the step using the acceleration value of the fixed number and the acceleration value from the acceleration sensor.

A storage picture generating unit (191) weight-adds an input picture and a storage picture to reduce the noise in a still picture portion. An area extraction unit (193) extracts a class tap from the input picture, while extracting a block from each of the input picture and the storage picture. A feature value detection unit (194) detects the dynamic range and the results of the waveform analysis from the class tap, while detecting the still/moving information of the subject pixel from the block. A class code detection unit (195) generates a class code which is based on the feature value. A table (196) outputs to an estimation calculating unit (198) sets of the prediction coefficients held by the table and which are associated with the class code. An area extraction unit (197) extracts prediction taps from the input picture and the storage picture. Using the sets of the prediction coefficients and the pixel information from the area extraction unit (197), the estimation calculating unit (198) sequentially generates pixel values y of an output picture.