52 results about "Peak detection algorithm" patented technology

The invention relates to a nanosecond detection system based on a random pulse time sequence of an ultra high-speed data acquisition card, and relates to computer application technology and data acquisition and processing technology, in particular to detection and processing technology for the random pulse time sequence. The system performs data acquisition and on-line detection based on a 1GS / s ultra high-speed A / D converting unit and an FPGA high-speed processing unit, and can quickly and accurately detect pulse time in a quick-logic narrow-pulse sequence. The detection for the pulse time is to calibrate the pulse time by pulse peak positions through a particularly designed PeakTDC hysteretic peak value detection algorithm carried on the FPGA, and the time accuracy is 1ns. The system can obtain TDC time data conversion of quick response random events in finite nanosecond random pulse sequences on a time bin axis, and performs the detection on multi-channel pulse signals on line and highly synchronously with high speed and large capacity.

The invention discloses a method and a device for demodulating a fiber bragg grating (FBG) sensor. The method comprises the following steps of: controlling a wavelength scanning laser device to generate narrow-band scanning laser rays with continuously changed wavelengths by using a computer; splitting beams of the narrow-band scanning laser rays generated by the wavelength scanning laser device; enabling a generated reflection spectrum to enter a photoelectric detector again via an optical fiber coupler to be converted into electric signals after the beam-split narrow-band scanning laser rays respectively enter the FBG sensor to be measured and a reflecting FBG comb filter with a temperature compensation package function via the optical fiber coupler, and acquiring the electric signals by the computer after the electric signals are amplified; obtaining wavelengths of peaks of the reflecting FBG comb filter with the temperature compensation package function by the computer through a peak-detection algorithm; calibrating the reflection spectrum of the FBG sensor by the wavelengths; and calculating an absolute wavelength value of the FBG sensor.

The invention discloses a video heart rate detection method removing interference of ambient light variation. Firstly a face area-of-interest data set and a background area data set are obtained, a united blind source separation technology is utilized to process the two data sets, and signal sources of ambient light variation that the data sets both have are extracted and set to zero, thereby obtaining a face area-of-interest data set free of interference of ambient light variation; secondly, face area-of-interest data of an optimal color channel is selected, and an ensemble average empirical mode decomposition method is utilized to obtain intrinsic mode components; and then all local intrinsic mode components of which frequency corresponding to maximum amplitude values are in a set heart rate range are determined to be a candidate intrinsic mode component set, the intrinsic mode component corresponding to the largest maximum amplitude value is determined to be the optimal intrinsic mode component, and a video heart rate is obtained through a peak detection algorithm. The video heart rate detection method provides a relatively accurate algorithm for non-contact heart rate detection, and has important application prospects in the aspects of clinical disease diagnosis and daily medical care.

The invention discloses a method for quantitative detection of an immunochromatographic test card. The method comprises the following steps: (1) placing an immunochromatographic test card to be tested on a detection light path of a first light source to acquire a first image data matrix Pic 1; (2) placing the immunochromatographic test card to be tested on a detection light path of a second light source to acquire a second image data matrix Pic 2; (3) selecting a reference zone to calculate the image difference matrix a Pic; (4) adopting the chromatographic peak detection algorithm to calculate the characteristic value; (5) calibrating the concentration of an object to be tested. The method for the quantitative detection of the immunochromatographic test card can eliminate the problem of baseline deflection caused by nonuniform lighting of the light paths, dead angles of a lens of a detector and the like, and meanwhile, can effectively inhibit spurious signal peaks brought by shadows, impurity particle interferents and the like, thereby improving the accuracy in distinguishing chromatographic peaks, enhancing the signal-to-noise ratio of the chromatographic peak of an immune marker and improving the accuracy and the sensitivity.

The invention discloses a step counting method capable of recognizing movement types. The method comprises the following steps that: the acceleration data of a person are acquired, and resultant acceleration is calculated; low-pass filtering and smoothing processing are performed on the resultant acceleration, waveforms corresponding to the resultant acceleration can be obtained; a preset dynamic wave peak detection algorithm is called to detect whether the waveforms belong to movement waveforms; and if the waveforms belong to the movement waveforms, a DTW (Dynamic Time Warping) algorithm is called to find out sample waveforms in a sample database which have the highest similarity to the waveforms, a movement type corresponding to the sample waveforms is the movement type of the person, and steps corresponding to the movement type is calculated according to the number of the wave peaks of the waveforms. The present invention also provides a mobile terminal and a storage medium. According to the prior art, only the total number of movement steps can be recorded, and step counting cannot be performed separately according to movement types, while, with the method, the mobile terminal and the storage medium adopted, the problem in the prior art can be solved.

The invention discloses an assessment method of auxiliary CRS-R scale auditory shock based on a brain-computer interface. The assessment method comprises following steps of: 1) selecting simulation, arranging and designing an experimental paradigm; 2), collecting signals; 3) performing data processing; 4) counting inspecting evaluation standards. The assessment method of auxiliary CRS-R scale auditory shock based on the brain-computer interface has following beneficial effects: based on an auditory extraneous experimental paradigm, mismatch negative waves MMN and P300, peculiar to human race, are induced; in combination with an auditory shock assessment method of a coma recovery scale CRS-R, scores of CRS-R auditory shock items are accessed by adoption of the brain-computer interface and a peak detection algorithm; and therefore, the method can not only be effectively used for assessment diagnoses of the coma recovery scale, tracking of recovery effect and selections of a prognosis treatment scheme but also provide scientific and objective detection data to the conventional scale diagnoses in order to ensure authenticity and effectiveness of detection results..

The embodiment of the invention relates to a spectral analysis method in the filed of elemental spectral analysis, which comprises the following steps of: locking the peak of a spectral peak as the mean initial value of a Gaussian function by using a peak-detection algorithm; using a peak value corresponding to the peak position of the spectral peak as a coefficient initial value of the Gaussian function; calculating the errors of a fit spectral peak area and the original spectral peak area under all spectral peak widths in the range of the whole energy spectrum, and calculating a variance initial value of the Gaussian function according to the spectral peak width corresponding to the error minimum; calculating the error of the fit spectral peak area and the original spectral peak area under each value of the mean value, the coefficient and the variance in the value range of the mean value, the coefficient and the variance, and calculating the mean value, coefficient and variance corresponding to the minimized error in all the errors to serve as the final characteristic parameters of the Gaussian function; and performing the spectral analysis by using the Gaussian function corresponding to the final characteristic parameters. The spectral analysis method improves the reproducibility of the spectral peak, and provides more accurate and detailed data for subsequent elemental analysis and quantitative analysis.

The invention discloses a drug cardiotoxicity detection analysis method based on a myocardial cell sensor. According to the drug cardiotoxicity detection analysis method, a high-performance and low-cost cardiac muscle cell sensor is constructed by adopting ex vivo myocardial cell culture; the change of pulsation images when myocardial cells mechanically pulsate is calculated and detected by adopting algorithms such as image acquisition, conversion of an RGB image into a gray level image, image binaryzation, image matrixing and peak detection, and the mechanical pulsation of the myocardial cells is quantized by using a difference value of the pulsation images, the detection on a rate, an amplitude and a pulsation interval of mechanical pulsation of the myocardial cells is realized; by analyzing the change of the mechanical pulsation state of the myocardial cells over time under the drug action, the cardiotoxicity of a drug is evaluated. Compared with an existing drug cardiotoxicity detection analysis method, the drug cardiotoxicity detection analysis method has the advantages of no marks, no loss, low cost, simple operating steps, and the like, and is capable of observing and evaluating the drug cardiotoxicity simply for a long time.

The invention discloses an unmanned aerial vehicle signal recognition and detection algorithm based on a Hash fingerprint. The method comprises the following steps: S1, acquiring a radio-frequency signal of a wireless signal (including an unmanned aerial vehicle) physical layer lead code, detecting a starting point, and extracting an envelope of a wireless signal lead code radio-frequency signal; S2, acquiring lead code feature waveform information of a wireless signal by adopting an improved peak detection algorithm, wherein the lead code feature waveform information comprises an envelope peak amplitude and position information; and S3, constructing a Hash fingerprint of an unmanned aerial vehicle signal according to the lead code feature waveform information, and performing fingerprint recognition. Through adoption of the algorithm, the feature waveform information of the wireless signal can be extracted according to different feature waveforms of the wireless signal lead code radio-frequency signal, and Hash fingerprint recognition is performed, so that a high unmanned aerial vehicle signal recognition rate is achieved.

A peak visualization enhancement system for use with a non-destructive inspection (NDI) instrument using a digital display which replicates the haloing effect of analog cathode ray tube (CRT) displays. A peak detection algorithm is provided which intelligently selects the peak values from within the uncompressed digitized waveform while taking measures to prevent noise spikes and the like from being identified as valid waveform peaks. The digital display then highlights the identified peaks, or a subset of the identified peaks, on the compressed waveform display. In this way the effect of bright spots (halos) about the zero slope points on a waveform displayed on an analog CRT is replicated in a digitally compressed waveform display.

The present invention discloses a terminal-based pedestrian positioning method and pedestrian positioning device. The method comprises: acquiring an initial position and an initial heading angle of apedestrian; identifying a real-time posture of a pedestrian carrying terminal; based on a preset correspondence, performing coordinate system conversion on acceleration data of a carrier coordinate system, and setting the axial acceleration or the acceleration modulus of the coordinate system corresponding to the real-time posture as the reference acceleration; preprocessing the reference acceleration, screening the preprocessed reference acceleration by using the peak detection algorithm, and collecting statistics of the number of steps of the pedestrian according to the screened peak; determining the step size and the heading offset of the pedestrian; and determining the target position of the pedestrian according to the number of steps, the step size and the heading offset, the initialposition, and the initial heading angle. According to the technical scheme of the present invention, the accuracy of counting the number of steps can be improved, the positioning accuracy of the pedestrian can be improved, and the technical scheme has high practical application value especially for indoor positioning and navigation.

The invention discloses a DSP (diarrhetic shellfish poison) detection and analysis method based on a cell image sensor. The method is characterized by comprising the following steps: establishing the cell image sensor which is high in performance and low in cost, acquiring an image, converting an acquired RGB (red green blue) image to a grayscale image, binaryzating the image, matriculating the image, detecting a peak value, detecting the variation of a pulse image of a myocardial cell when in mechanical pulse, and detecting the mechanical pulse rate, pulse range and pulse interval of the myocardial cell; establishing a standard graph by detecting the response of the cell image sensor to different standard sample working solutions of the shellfish diarrhetic poisons in different concentrations; and detecting the response of the cell image sensor to the shellfish diarrhetic poisons of unknown concentration, comparing the detected response result with the standard graph, and semi-quantitatively calculating the concentration of the poisons. Compared with the existing shellfish diarrhetic poison detection and analysis method, the method is low in cost, simple in operation and capable of directly evaluating the toxicity of the poisons for a long time.

The invention relates to an apparent density peak detection algorithm based on double-check. The apparent density peak detection algorithm based on double-check comprises the following steps that: a local density peak point is found out by calculating the distance between every two data concentration points to be clustered and outer densities of all points; and then, an apparent density peak point is finally found out by calculating the inner density of the local density peak point. Because of calculation of the inner density, the flexibility and the complex data processing capability of a density-based clustering algorithm are improved; the apparent density peak detection algorithm based on double-check can effectively increase the accuracy rate of the traditional density-based clustering algorithm and improve the bit error rate performance of the system; and thus, a relatively low error floor can be obtained.

A method and apparatus taught herein reduce the peak-to-average ratio (PAR) of a complex-valued signal based on detecting peaks in the signal that are above a peak threshold, characterizing the detected peaks in Cartesian coordinates, generating cancellation pulses in Cartesian coordinates based on the detected peak characterizations. PAR reduction processing continues with canceling the detectedpeaks by combining the cancellation pulses with a correspondingly delayed version of the signal. Advantageously, peak detection may be performed in polar form using a computationally efficient peak detection algorithm that avoids calculation of the I and Q peak waveforms unless a signal peak beyond a defined threshold is present. In one or more embodiments, the generation and use of asymmetric and / or shaped cancellation pulses offers further performance advantages.

The invention discloses a myocardial cell mechanical beating detection method based on optical image analysis. The method comprises the following steps: detecting the change of beating images of myocardial cells in mechanical beating by adopting image treatment and analysis techniques such as image acquisition, RGB (Red, Green, Blue) image-to-gray-image, image binaryzation and image matrixing by virtue of a myocardial cell mechanical beating detection system, and quantizing myocardial cell mechanical beating by adopting a beating image difference value to achieve the detection of a mechanical beating curve of the myocardial cells; and according to the obtained mechanical beating curve of the myocardial cells, calculating the beating rate and amplitude of the myocardial cells by virtue of a peak detection algorithm, and analyzing a mechanical beating state of the myocardial cells. Compared with an existing myocardial cell mechanical beating detection method, the myocardial cell mechanical beating detection method based on optical image analysis disclosed by the invention has the advantages that the method is mark-free and nondestructive, is low in cost and simple in operation step, and can be used for synchronously and directly detecting a cell beating image and analyzing the cell beating state, and the like.

The invention discloses an ultra wideband radar identity recognition method based on a breathing sample space. The method comprises the steps that an ultra wide band radar sensor collects ultra wide band radar echo signals with human body breathing characteristics returned according to a transmission pulse of a fixed period; after phase noise correction and filtering preprocessing are carried out on the ultra-wideband radar echo signal, an energy characteristic peak detection algorithm is adopted to detect the preprocessed ultra-wideband radar echo signal so as to determine a distance unit where a target is located; the method also includes extracting a one-dimensional breathing time-domain signal of a distance unit where the target is located, filtering the one-dimensional breathing time-domain signal, and performing fast Fourier transform on the filtered breathing time-domain signal to extract a breathing frequency; dividing the preprocessed ultra-wideband radar echo signal according to the respiratory frequency to obtain a series of sub-matrixes as samples in a respiratory sample space; using a convolutional neural network and a sample for modeling a breathing sample space to obtain a target identity recognition result, so that identity recognition can be carried out on a target user according to breathing features.

The invention provides a multi-camera-based non-contact type vital sign parameter detection method. The method is characterized in that P cameras are used for simultaneously collecting video signals of the upper half of the human body, and color channel data containing the largest number of region-of-interest pixels in the P cameras is selected to form a pixel mean value optimization set; then, anoverall average empirical mode decomposition method is adopted for decomposition, and the optimal intrinsic mode component is determined by setting a vital sign parameter range; finally, a peak valuedetection algorithm is adopted for the best intrinsic mode component to obtain a vital sign parameter detection result. The invention provides the multi-camera-based non-contact type vital sign parameter seamless detection method so that the defect of a non-contact type vital sign parameter detection technology using a single camera can be overcome, and therefore non-contact, continuous and accurate vital sign parameter detection of clinical disease diagnosis and treatment and daily health monitoring is achieved.

An embodiment of the invention relates to the technical field of medical monitoring, in particular to a blood pressure monitoring device, method and system. The device applied to monitoring equipmentcomprises a signal acquiring module, a time delay acquiring module and a blood pressure calculation module and is characterized in that the signal acquiring module is used for acquiring the ballistocardiogram signal, collected by first collecting equipment, of a user and the pulse wave signal, collected by second collecting equipment, of the user, wherein the collecting time of the first collecting equipment is synchronous with the collecting time of the second collecting equipment; the time delay acquiring module uses a peak detection algorithm to calculate the peak time delay of the ballistocardiogram signal and the pulse wave signal according to the ballistocardiogram signal and the pulse wave signal to serve as the pulse wave signal conduction time; the blood pressure calculation module is used for calculating according to the pulse wave signal conduction time to obtain the blood pressure data of the user. By the blood pressure monitoring device, method and system, continuous and real-time blood pressure monitoring can be achieved.

A colon cavity inner capsule system positioning device is composed of an in-vivo capsule with an MEMS magnetic field sensor, and an in-vivo system wirelessly connected with the in-vivo capsule and transmitting magnetic field intensity information. An in-vitro system comprises four permanent magnets and a data processing mechanism. The collected magnetic field intensity information is processed, and an in-vivo capsule is positioned; that is, the magnetic field intensity is determined by the distances between the capsule and the four permanent magnets, and the closer the device gets to any permanent magnet, the higher the detected magnetic field intensity is. The change situation of the magnetic field intensity can be monitored in real time, and the position of the capsule can be accurately positioned and the moment when the capsule passes by a colon cavity can be determined through a denoising preprocessing and peak value detecting algorithm.

The invention provides an FBG optical fiber sensing demodulation system for marine environment monitoring. The system comprises a signal input source and a signal sensing module, and further comprisesa demodulation technology module and a signal processing module. The demodulation technology module is used for receiving and demodulating a reflected optical signal output by the signal sensing module, outputting a demodulated transmitted optical signal, and converting the transmitted optical signal into an electrical signal, the signal processing module collects the electrical signal output bythe demodulation technology module, and information of demodulated monitored variable is obtained through a signal processing algorithm. The system is based on a tunable optical fiber FP filter, adopts a cascade algorithm combing a peak-detection algorithm and an adaptive filtering improvement algorithm to improve the demodulation accuracy and improve the system performance in the premise of not changing hardware facilities.

A method of determining bearing preload by vibration measurement including mounting the bearing on a vibration tester, the outer ring clamped preventing rotation, mounting a sensor proximate the outer ring to measure vibration, the bearing inner ring rotated to excavate eigen-frequencies, the measured vibration data transmitted from the sensor to a computer workstation, the computer workstation performs a numerical FFT transforming data to Frequency Domain, spectral data from the FFT analyzed with the computer workstation, a peak detection algorithm determines the peaks that are the various modes of the outer ring, the modes are sorted and main modes identified, numerical relationship is obtained for each mode between the resonance and preload, the mode relationships are compared to one or more references, a match between the numerical relationships for each mode and the ideally referenced graph modes indicates a correct preload is determined. Also, a system for carrying out the method.

The invention discloses a substance identification method of an ion mobility spectrum (IMS) detection instrument based on an ion diagram sequence. The method comprises the following steps: 1. executing preliminary substance identification for one time on a preprocessed ion diagram by utilizing a peak-detection algorithm, and storing substances matched in substance identification at this time; 2. continuously executing step 1 at a time interval of Delta t until times of preliminary substance identification reach preset times M, wherein, M is a natural number which is greater than 2; and 3. eliminating interfering substances from the substances matched in preliminary substance identification for M times. In the invention, for certain multi-peak substances, information such as peak quantity, peak position and the like changes with time, so a false alarm is given if only based on the identification result of the preprocessed ion diagram, which causes misguidance on an inspector using the detection instrument. By utilizing the substance identification method based on the ion diagram sequence, probability of the false alarm can be lowered so as to reduce misguidance on the inspector.

A system and method to extract the timing of ECG events without reliance on ECG. The system and method are based on effects of scalp pulsation (due to blood flow) on electrode location. The electrodes in the system with the closest proximity to the facial arteries are re-referenced to create a [Mean Left-Mean Right] signal (LRM). A constrained peak detection algorithm is then used to find the BCG events. Finally, an automatic error checking and correction algorithm based on inter-beat timing is applied.

The invention discloses a method for demodulating impact signals on the basis of all-digital peak detection, and belongs to the field of fault diagnosis for rotary machinery. The method has the advantages that in order to overcome shortcomings of poor instantaneity of an envelope solving procedure implemented in the traditional Hilbert demodulation method and low fault detection rate under a low signal-to-noise ratio condition, an all-digital peak detection algorithm with a structural element of AXe(-t / tau) is adopted in the method and is excellent in instantaneity, applicable to embedded equipment and high in noise immunity, excellent diagnosis results can be realized when the method is applied to rotary equipment working in complicated environments of industrial fields, and the method has an important economic significance and high engineering application value.

An embodiment of the invention relates to a method and device for detecting signal quality based on difference wave ratio. The method includes: acquiring a PPG signal; sampling signal data of the PPGsignal according to a signal sampling frequency threshold to generate a PPG data sequence; taking total number of signal point data included in the PPG data sequence as total number of signals; performing a peak point detection on the PPG data sequence using a peak detection algorithm to generate a peak point sequence; performing quality detection on the number of signals per unit time according to the peak point sequence and the threshold range of the number of signals per unit time, and generating a first quality detection result; when the first quality detection result is qualified, performing PPG signal width calculation according to the peak point sequence to generate a signal width sequence; performing quality detection on the difference wave ratio according to the signal width sequence, the difference wave deviation multiple threshold and the difference wave ratio threshold, and generating a second quality detection result; and when the second quality detection result is qualified, setting the PPG signal quality status to qualified.

The invention discloses a substance identification method of an ion mobility spectrum (IMS) detection instrument based on an ion diagram sequence. The method comprises the following steps: 1. executing preliminary substance identification for one time on a preprocessed ion diagram by utilizing a peak-detection algorithm, and storing substances matched in substance identification at this time; 2. continuously executing step 1 at a time interval of Delta t until times of preliminary substance identification reach preset times M, wherein, M is a natural number which is greater than 2; and 3. eliminating interfering substances from the substances matched in preliminary substance identification for M times. In the invention, for certain multi-peak substances, information such as peak quantity,peak position and the like changes with time, so a false alarm is given if only based on the identification result of the preprocessed ion diagram, which causes misguidance on an inspector using the detection instrument. By utilizing the substance identification method based on the ion diagram sequence, probability of the false alarm can be lowered so as to reduce misguidance on the inspector.

A multistage audio transient-and-stable state determining method based on variance and time domain peak value comprises the steps of performing frame dividing on an original audio signal through using 1024 sampling points as a unit; calculating a mean value and the variance on each signal frame, comparing the variance with a preset variance threshold, setting the determining mark of the signal frame of which the variance is smaller than or equal with the variance threshold to one, and outputting a stable state frame mark; determining the signal frame of which the variance is larger than the variance threshold according to a peak value detecting algorithm; determining the determining result of the peak value detecting algorithm, if the determining mark is one, outputting the stable state frame mark, and if the determining mark is zero, outputting a transient state frame mark. The multistage audio transient-and-stable state determining method determines the transient-and-stable state of audio by means of the variance and the time domain peak value of the signal. The obtained transient-and-stable signal is used for adaptive window switching. Low complexity and high accuracy in determining the transient-and-stable state are realized. Lower time complexity is realized. Furthermore detection for the signal with relatively low energy can be prevented. Detecting accuracy is improved.