334 AcqKnowledge 4 Software Guide Detect and Claify Heartbeat Thi robut QRS detector i tuned for human ECG Lead II ignal. It attempt to locate QRS complexe and place an event near the center of each QRS complex to identify the type of heartbeat event: Normal The beat wa recognizable a a valid heartbeat falling in a human heartbeat rate. PVC The beat wa horter than the beat around it and may be a pre-ventricular contraction. Thee event can be found in the Hemodynamic > Beat ubmenu of the event type liting. Unknown The beat wan t recognizable a a valid heartbeat. Thi may occur on the firt beat prior to the QRS detector locking onto the ignal. It may alo occur if tracking i lot due to change in ignal quality. The Cycle/Peak detector may be ued with thee event to perform further cardiac analyi. Locate Human ECG Complex Boundarie Locate Human ECG Complex Boundarie perform ECG waveform boundary detection for human ECG Lead II ignal; ECG ignal mut be ampled at 5 khz or below to be analyzed with thi claifier. It will attempt to locate the boundarie of the QRS, T, and P wave and will define event for each individual complex. It will attempt to inert the following event; all of thee complex boundarie can be found in the Hemodynamic > ECG Complexe ubmenu of the Event Type liting. Wave Type Event Placement & Decription QRS Onet Peak End Before the beginning of the Q wave At the top of the R wave After the end of the S wave T-wave P-wave Onet Peak End Onet Peak End At the onet of T At the peak of the T wave Note: Thi may not be a poitive peak if the T-wave i inverted. If the T-wave eem to be bi-phaic, two T-wave event will be inerted and the event decription will indicate that the T-wave i bi-phaic. At the end of T At the onet of P At the top of the P wave Note: Thi may not be the abolute maximum, but rather the likely center of P. At the end of P The Cycle/Peak detector may be ued with thee event to perform further cardiac analyi. Locate Animal ECG Complex Boundarie Locate Animal ECG Complex Boundarie optimize the ECG waveform boundary detection for animal input. Smaller animal uch a mice often lack a detectable T wave, o in the etup dialog the T wave boundarie are diabled by default. If appropriate to the experiment, T wave detection can be applied by enabling the Define T wave boundarie checkbox. The average heart rate can alo be cutomized to reflect the normal range of a particular animal ubject. (The default rate i 600 BPM.) Viit the online upport center at www.biopac.com
Part C Analyi Function 335 Heart Rate Variability New parameter etting for the HRV algorithm function better on horter ECG ignal and correpond more cloely with other implementation. Heart rate variability i the examination of phyiological rhythm that exit in the beat-to-beat interval of a cardiac ignal. Heart rate variability ait in performing frequency domain analyi of human ECG Lead II data to extract tandard HRV meaure. The HRV algorithm in AcqKnowledge 3.9 and above conform to the frequency domain algorithm guideline a publihed by the European Heart Journal. HRV proceing in AcqKnowledge conit of three tage: 1. The RR interval are extracted for the ECG ignal. A modified Pan-Tompkin QRS detector i ued. 2. The RR interval are re-ampled to a continuou ampling rate in order to extract frequency information. Cubic-pline interpolation i ued to generate thi continuou time-domain repreentation of the RR interval. 3. The frequency information i extracted from the RR interval and analyzed to produce tandard ratio. Power um are reported in unit of ec 2. A Welch periodogram i ued to generate the Power Spectral Denity (equivalent to Tranform > Power Spectral Denity). AcqKnowledge 4 Software Guide
336 AcqKnowledge 4 Software Guide The initial implementation of the HRV algorithm wa primarily for ue with long duration recording. HRV algorithm improvement allow for further cutomization to the algorithm: Windowing type for FFT ued to contruct the PSD may be changed between Hamming, Hanning, and Blackman Overall window length for egmenting ource data for individual FFT to include in PSD average may be modified Length of the individual FFT in the average can be manually pecified Scaling ha been changed for PSD, which are now caled relative to the ampling frequency Summary of power in individual frequency band ha been changed Intead of a traight um, an average power value i now reported Power at endpoint i halved (e.g. divided by 2) Sympathetic/Vagal ratio may optionally include the very low frequency band in the total power etimate The modification to the HRV algorithm that affect it power pectrum etimation have alo been applied to the PSD tranformation. After electing Analyi > Heart Rate Variability, chooe the appropriate tab() and etablih etting. Preet control, Tranform entire wave checkbox, and OK/Cancel button apply acro all of the tab. Preet The preet menu can be ued to ave a variety of HRV etting, including: beat detection parameter, pline reampling frequency, and frequency band range. Chooe a preet from the popup menu to apply it etting. To contruct a new preet with the currently diplayed etting, chooe Add New Preet. A default preet for adult human ubject i upplied. IMPORTANT Recording good data i eential for performing HRV analyi. The protocol for data acquiition, filtering, artifact detection and correction in Application Note 233 reult in great improvement in HRV analyi. Reult reveal that even a ingle heart period artifact, occurring within a 2-min recording epoch, can lead to error of etimate heart period variability that are coniderably larger than typical effect ize in pychophyiological tudie. Bernton & Stowell, 199 See Application Note 233 Heart Rate Variability Preparing Data for Analyi Uing AcqKnowledge (online at www.biopac.com) The note explain how to optimize ECG R-R interval data for Heart Rate Variability tudie by uing a template matching approach. It alo explain how to identify erroneou R-R interval value caued by ignal artifact and how method for correcting the error by uing the tool in the AcqKnowledge oftware. The note explain how to: A. Record good ECG data B. Prepare data for the tachogram 1. Filter the ECG data 2. Tranform the data uing Template Correlation function C. Create a tachogram D. Identify problem with the tachogram data E. Correct tachogram data Viit the online upport center at www.biopac.com
Part C Analyi Function 337 RR interval Select a method to locate R wave: QRS Detector or Event. QRS detector The heart rate variability implementation ha a built-in QRS detector. The detector doe not run on raw ource data; it ue a modified Pan-Tompkin algorithm to normalize the ECG data to 1, whereby the peak amplitude of the highet R-wave repreent 1. Ue the tachogram output to examine the output of the QRS detector. R wave threhold The detection threhold mut be pecified in term of percentage of maximum R peak level; thi help to clarify the unit in which thi threhold i expreed. The default threhold level of.5 hould place the threhold in the middle of the R-wave, which hould function on a wide range of data et. If the R-wave amplitude varie a lot, it might be neceary to adjut the threhold level. o R wave threhold i expreed in normalized unit, which are in the range (-1, 1): poitive for poitive R wave peak. The maximum voltage in the ignal map to 1.0 and the minimum voltage in the ignal map to -1.0. Pan J and Tompkin WJ. A Real-Time QRS Detection Algorithm. IEEE Tranaction on Biomedical Engineering 32(3):230-236, 1985. Event R-wave peak will be located uing event already in the graph of the channel of data to be analyzed. Thi aume a ingle event i placed at each R-wave peak and that all of the R-peak event are of the ame event type. When uing event, the built-in QRS detector i not ued; the exact poitioning between the event on the channel i ued to extract the RR interval. By uing event, it i poible to ue other QRS detector within AcqKnowledge for performing HRV analyi. It i alo poible to apply pectral HRV-tyle analyi to data in other domain a long a interval can be reduced to event. Spline reampling frequency For highet accuracy, et to no le than twice the topmot frequency of the very high frequency band. AcqKnowledge 4 Software Guide
338 AcqKnowledge 4 Software Guide Frequency Band Enter the tart and end of each pecified frequency band to adjut the boundarie of the frequency analyi. They are preet to the frequency range recommended by the European Heart Journal. Output of derived parameter i preented in a dialog and may alo be pated a text to the Journal. Very high frequency band, uually ued in rat tudie, i diabled if the pline reampling frequency i le than the upper bound of the very high frequency range. PSD Option PSD Option etablih parameter for the power pectral denity tranformation ued to compute the pectrum from the interpolated tachogram; the option contained in thi tab mirror the control of the Analyi > Power Spectral Denity tranformation. The ue of linear detrending in each individual egment of ource data prior to the windowed periodogram analyi can be enabled or diabled. When diabled, the algorithm may be tuned to correpond to implementation that do not apply linear trending, uch a MATLAB, which ue windowing only. The ame PSD option are available via Analyi > Power Spectral Denity o uer can regenerate the pectrum from either the raw or interpolated tachogram output a neceary. After the uer modifie the parameter for the PSD tranformation, thoe parameter will become the new default value each time the dialog i diplayed. When the application i relaunched, the default etting will be ued (uer change are not peritent). Viit the online upport center at www.biopac.com
Part C Analyi Function 339 Window Window ize Ued to change the window that i applied to each egment of the ource data prior to computing the PSD to be included in the average. Include the following option: Hamming Hanning Blackman The pecified number of ample mut be a power of two. Note that the window function i applied to the entire window width of the data; uing a ubet of the windowed data will not include the final portion of the windowed data. If the FFT ize i le than the window ize, only a ubet of the windowed ample data will be ued. Automatic If elected, the window ize i elected automatically depending on the ize of the ource data. For a data length of n ample, chooing thi radio button will ue the window ize: Manual L = n 4.5 If elected, the window ize will be input manually by the uer in the aociated edit field. The window ize mut be greater than three and mut be le than the length of the data election. Uer will be warned on invalid window ize when attempting to click OK. Overlap length After each individual FFT, the window of ource ample i hifted over by a certain amount to compute the next FFT, o there i an overlap of ource ample in ucceive window of ource for the next FFT in the average. Automatic If elected, the number of ample to overlap ucceive window will be computed automatically. Given a window length L computed according to the window width choice, chooing thi radio button will ue an overlap number of ample: Manual L 2 elected, the number of ample to overlap ucceive window of ource data. Overlapping reduce windowing artifact The overlap length mut be poitive and mut be le than the window ize. Uer will be warned on invalid overlap length when attempting to click OK FFT width Automatic If elected, the number of point to ue for each individual FFT will be computed automatically. Given a window length L computing according to the window width choice, the number of point in the FFT will be et to: Manual The number of point in the FFT i et to 256 if the window width i le than 256. Otherwie the length i et to the next power of two higher than the window width. If elected, the number of point in the FFT will be pecified manually in the edit box to the right of the radio. The number of point in the FFT will be required to be a poitive power of two. It i recommended that the FFT length be et larger than the window ize. If longer than the window ize, zero point padding i ued. Uer will be warned on invalid FFT number of point when attempting to click OK. If the uer input a number of point for the FFT that i horter than the window width, a confirmation dialog will be diplayed to the uer warning that the windowing i horter than the requeted FFT width and aked if they want to continue. AcqKnowledge 4 Software Guide
340 AcqKnowledge 4 Software Guide Ue linear detrending for each window Detrend each egment independently Tranform entire wave When enabled, linear regreion detrending i applied for each individual egment prior to the FFT computation. When diabled, windowing only i applied. Thi option i only available when Ue linear detrending i enabled. When thi option i enabled, detrending i applied independently for each egment; when diabled, detrending from the previou egment will be incorporated into the next egment. When enabled, the entire waveform i delayed. When unchecked, only the elected area i delayed. If there i no election in the graph, the checkbox i enabled and dimmed. A the election change in the graph with the election palette, the tate of thi checkbox i updated. Improvement to PSD Option (AcqKnowledge 4.3 and higher) The PSD output i now caled o power value are caled by the ampling rate. That i: PSD new = PSD old f Reporting a um for a frequency range when computing the power in an individual band ha been changed. Given a frequency range f, f low high define the et S of all ample of the PSD where S = PSD f,,psd. Define the um of the power within the frequency range a: low f high S f high flow i= S 1 S1 S f 2 2 2 low, f high = + Si +. Thi applie the caling factor to a um of the i= S 1 frequencie in the frequency range, with the magnitude at the endpoint divided by 2. Previou verion would perform a direct um of all amplitude within the frequency band. Reult reporting ha been changed for the overall ratio. The VLF ection i now included in the ratio. A = v, v =,, and new VLF ratio ha been introduced. Define, = low, high. The new VLF ratio i: ratio defined a: ratio = v + + v v low = v high + v +. The new vagal ratio i defined a: previou algorithm define the ympathetic ratio a: ratio the vagal ratio a: ratio =. old + old = + low high. The new ympathetic ratio i ratio = v + +. The. The previou algorithm define Viit the online upport center at www.biopac.com
Part C Analyi Function 341 Output Create tandard reult preentation graph or ae performance of the HRV algorithm. Output option allow acce to intermediate computation data for algorithm validation and/or meaurement. RR Interval table If the combined output formula i elected, the analyi output will contain an additional line of text: VLF Ratio with the correponding percentage. Spectrum Diplay the power pectrum denity (PSD) etimation from which the PSD ummation and ympathetic/vagal ratio are computed. Raw tachogram Plot the raw R-R interval found by the QRS detector. Perform tatitical HRV meaure on the R-R interval without exporting the textual R-R table to excel. Interpolated tachogram Plot the reampled R-R interval after cubic pline interpolation i applied and extract the PSD from thi data. Gatric Wave Analyi Gatric Wave Analyi ue autoregreive time-frequency analyi to determine the claification of gatric wave preent in an EGG ignal. The ingle wave analyi determine the percentage of gatric wave that fall within the frequency band correponding to normal, bradygatric, and tachygatric wave. The analyi alo indicate the percentage of wave that fall outide of thee boundarie and are arrhythmia. The frequency band are expreed in unit of contraction per minute and may be adjuted by the uer. Preet for commonly ued ubject and wave type are predefined; you may extend thee preet with your own. AcqKnowledge 4 Software Guide
342 AcqKnowledge 4 Software Guide Gatric Wave Coupling Gatric Wave Coupling take two EGG ignal and ue autoregreive technique to claify the contraction in thoe ignal according to uer-configurable frequency band (imilar to ingle channel Gatric Wave Analyi). In addition to providing claification information for the two ignal, Gatric Wave Coupling provide a meaure of the percentage of coupling between the two ignal thi meaure that can be ued to determine the amount of low-wave propagation acro the tomach. Chao Analyi The Chao analyi package ait the uer in exploring the chaotic nature of data, including meaurement election and viualization of time domain attractor in the data. Detrended Fluctuation Analyi Modified root mean quare analyi, ueful for evaluating e-imilarity in a long-term, non-tationary data erie. Source data i mean-adjuted and then integrated; it i then plit up into n egment of equal length, and in each egment, via linear regreion, the bet fit leat quare line i computed. For a particular value of n and a number of ample N, the characteritic fluctuation of the piecewie linear fit y n. i defined a: F n 1 N N k 1 y k y n k 2 F(n) i evaluated over a uer-pecified range for the number of diviion. n will equal the total length divided by the number of diviion. A log-log plot of the interval width n in ample veru the correponding value of F(n) will be created. If a linear relationhip appear to exit in thi graph, then the ource ignal diplay ome form of e-imilarity. The lope of the line in thi graph i related to the caling exponent. For more information on Detrended Fluctuation Analyi, ee http://www.phyionet.org/phyiotool/dfa/ Viit the online upport center at www.biopac.com