S1 Document.
Contents
1. RIPScore estimates standard deviations using the bootstrap method 4 kjstd an M by 6 vector with the estimates of pattern specific standard deviation of kappa for each of the M training sessions RIPScore estimates standard deviations using the bootstrap method Each column corresponds to one the 6 unique pattern types coll Pause col2 Asynchronous breathing col3 Movement artifact col4 Synchronous breathing col5 Sigh col6 Unknown kcil deprecated kcih deprecated kjcil deprecated kjcih deprecated o ScoredSamples a 1 by 2 cell array with the number of samples scored in each session Coll Level 1 Col2 Level2 Each cell is a 1 by M vector where M is the number of training sessions o PracticeTime a 1 by 2 cell array with the time in seconds required to complete practice in each session Col1 Level 1 Col2 Level2 Each cell is a 1 by M vector where M is the number of training sessions o IterationTime a 1 by 2 cell array with the time in seconds required to complete each session Coll Level 1 Col2 Level2 Each cell is a 1 by M vector where M is the number of training sessions savepath a string with the path to the directory where this file is saved savename a string with the name of this file RIPScoreVersion a string with the version of RIPScore that created this file WorkingSession a struct with the following runtime fields isActive a flag indicating if the trainee hasn t finished the cur2. end a C by 1 vector with the end time of the segment linked to the comment 12 17 o O O eventID a C by 1 vector with the index of the linked segment as it appears in SCORING Events comment a 1 by C cell array with the comments assigned to the linked segments ElapsedTime deprecated Completed a flag indicating whether this data record has been completely scored or not FileName a string with the name of this file RIPScoreVersion a string with the version of RIPScore that created this file currentTime a scalar with the latest Epoch Start Time 3 Trainee data e g trainee TEST mat This is a file with a summary of the training results from scorer TEST The file contains the variables described next TRAINEE A struct with the following fields gt O O o Scorer astring with the scorer s ID level an integer indicating the latest scorer s training level iteration a 1 by 2 vector with the last session completed in level 1 col1 and level 2 col2 InterAgreement a 1 by 2 cell array with estimates of the accuracy performance estimated using the Fleiss kappa statistic 2 3 in level 1 col1 and level 2 col2 Each cell is a struct array with the following fields k a1 by M vector with the kappa estimate from each of the M training sessions kj an M by 6 vector with the pattern specific kappa estimate from each of the M training sessions Each column corresponds to one the 6 unique pa
3. the ribcage signal generated for this session AB an N by 1 vector with the abdomen signal generated for this session PP an N by 1 vector with the photoplethysmography signal generated for this session SA an N by 1 vector with the blood oxygen saturation signal generated for this session State an N by 1 vector with the actual pattern for each sample in DATA EventID an N by 1 vector with the ID of the segment each sample in DATA belongs to IsTestSegment an N by 1 vector zero valued for samples in the training stage and one valued for samples in the evaluation stage RIPScoreVersion a string with the version of RIPScore that created this file 15 17 VI List of Acronyms McCRIBS McGill CardioRespiratory Infant Behavior Software RIP Respiratory Inductive Plethysmography 16 17 VII References 1 Robles Rubio CA Bertolizio G Brown KA and Kearney RE 2015 Scoring Tools for the Analysis of Infant Respiratory Inductive Plethysmography Signals Submitted to PLoS One 2 Fleiss JL 1971 Measuring nominal scale agreement among many raters Psychol Bulletin 76 378 382 3 Cardillo G 2007 Fleiss es kappa compute the Fleiss es kappa for multiple raters MATLAB CENTRAL The MathWorks Inc 4 Efron B and Tibshirani RJ 1993 An introduction to the bootstrap New York etc Chapman Hall 17 17
4. 17 MI Quick Start A Description RIPScore is an open source interactive software application for manual scoring of infant Respiratory Inductive Plethysmography RIP data A detailed description of the analysis that can be performed using RIPScore is in 1 RIPScore was developed in MATLAB The MathWorks Inc Natick MA USA B Required Libraries It is necessary to obtain the following libraries to use RIPScore 1 McCRIBS McGill CardioRespiratory Infant Behavior Software tools These tools are open source functions developed in MATLAB and are available for download free of charge at github com McCRIBS Download the tools and save them in the directory C McCRIB McCRIBS 2 A library of true pattern segments as defined in 1 This library is available for download free of charge at datadryad org for details see 1 Download the data and save them in the directory C McCRIB Data C Run RIPScore The following steps provide a guide to start using RIPScore with default configuration parameters 1 Open MATLAB 2 Setup the McCRIBS working environment in MATLAB by running this code Path to the McCRIBS tools directory downloaded from github com SourceCodeRoot C McCRIB McCRIBS Path to the Data directory downloaded from datadryad org DataRoot C McCRIB Data Setup the working environment cd SourceCodeRoot Utilities setMcCRIBS Env SourceCodeRoot DataRoot McCRIB DATA ROOT getenv McCRI
5. B DATA ROOT The Data directory Go to RIPScore root directory cd SourceCodeRoot RIPSCORE RIPScore 3 Start the application by typing RIPScore in the MATLAB command window 4 RIPScore will load with the pre defined default configuration Blind Scorer Mode Click OK in the following screen 2 Welcome oO x RIPScore Version 1 2 Copyright c 2015 Carlos Alejandro Robles Rubio Karen A Brown and Robert E Kearney McGill University All rights reserved 5 17 5 RIPScore will then ask for Scorer Identification Select Add New Please enter your Scorer ID eg 5C1 Scorer ID y _ em 6 Type the Scorer ID in the text box e g TEST and click OK Please enter your Scorer ID e g SC1 Scorer ID TEST OK 7 RIPScore will display the number of files available for scorer TEST to analyze Click OK You have 2 of 2 files left 8 At this point RIPScore will randomly select one of the files left and load it for scorer TEST to analyze 9 Since this is the first time scorer TEST will analyze the current file RIPScore will output the following message Be This is the first time you score this file 10 Click OK RIPScore will load in Visualization Mode Scorer TEST is ready to analyze the data 11 For a detailed description of the main screen controls and their functionalities see 1 12 In this default configuration the scoring results are stored at C McCR
6. IB McCRIBS RIPSCORE scored 6 17 13 Also the sample data records are loaded from C McCRIB McCRIBS RIPSCORE data These records constitute brief segments of infant cardiorespiratory data pre processed by inserting segments with known true patterns using the script preprocess data records m The original data records were part of the infant data described in 1 14 RIPScore will save a backup of the analysis every 5 min 7 17 IV Configuration By default RIPScore is configured to start in Blind Scorer Mode a mode that randomly selects the next record to analyze from a directory containing sample data records For project specific needs it may be necessary to use alternative configurations There are 2 ways to trigger RIPScore s configuration process which are 1 Run the function RIPScore_setParameters with parameter C McCRIB McCRIBS RIPSCORE RIPScore or 2 Delete the file C McCRIB McCRIBS RIPSCORE RIPScore cnf mat and run RIPScore This will initialize an interactive configuration process where RIPScore will ask the questions described next 1 Select RIPScore Mode Riki Ed Select RIPScore Mode Administrator open Training Set the Mode in which the application will run gt Administrator open RIPScore runs in Scorer mode it lets the user load any RIPScore data file This mode can be used for non randomized scoring and to review the scores from different scorers gt Blind scorer def
7. RIPScore v1 2 User Manual Copyright 2015 Carlos Alejandro Robles Rubio Karen A Brown and Robert E Kearney McGill University Table of Contents l LICENSE T E ENE E EE E E A EE T EET ETT 3 Il ACKNOWLEDGEMENT os ceias cocssceissiscasessccoseccocsctnsccesecusseseseekescoddecoteedevevesvenassbeccscsesncsesiecdcteossesecessevsedeedes cess 4 ll QUICKSTART vcs scowescercacosovcosteccssncecastevechceeteovedcesauecescecsesecedostesoueceoseeevtesevacsevacecducecotoosecobeccosceesescesecenceasves 5 As DESCRIPTION cota renea tase cia shoves e a aa sash ave A dances Sochaeobiva did da 5 B REQUIRED LIBRARIES ii aid 5 C ANAA ALLEN EEEE E AE TEE ETA EEE EEE EEE EANES 5 IV CONFIGURATION laeras ea O a ea O E Ea E a E Oa aae o ESSE eSa eask isei ReiS en 8 V DATA A A E AT T E A A T E E T E A A 12 A AT EEEE RE E E AE AE E E E ONEA R T EE E PE NE E A O E A E 12 B OOH U a EE EE A a AAEE RAE AA ER EAE 12 VI LISTTOFACRONYMS conocio ceon e inc aeae aa a aa N ee iaoea Seea sea andan one akore irasi Sosa 16 Vil REFERENCES anian onea O 17 2 17 I License Copyright c 2015 Carlos Alejandro Robles Rubio Karen A Brown and Robert E Kearney McGill University All rights reserved Redistribution and use in source and binary forms with or without modification are permitted provided that the following conditions are met 1 Redistributions of source code must retain the above copyright notice this list of conditions and the follo
8. ault RIPScore runs in Scorer mode it keeps the file selection blinded from the user by automatically and randomly selecting the next file to analyze gt Training RIPScore runs in Training mode it generates simulated data provides practice with interactive feedback for the user and evaluates the user performance 2 Scoring results path Iof ES Select directory where scoring results are saved Choose create a directory where the scoring analysis results will be saved In the default configuration this directory is C McCRIB McCRIBS RIPSCORE scored After selecting the directory RIPScore will output the full path to it Jof ES Scoring results will be saved to C McCRIB McCRIBSSRIPSCORE scored 8 17 3 Data records path lolx Select directory where data records are stored Choose create a directory where the raw data to be analyzed is saved In the default configuration this directory is C McCRIB McCRIBS RIPSCORE data After selecting the directory RIPScore will output the full path to it Jof x Data records will be loaded from CAMCCRIBAMCCRIBSARIPSCOREA datas 4 Set Environment Variables of x Enter Epoch Length s o Enter Sampling Frequency Hz 0 conca Enter the length of the data epoch displayed on the screen default is 30 s and the sampling frequency of the data default is 50 Hz Click OK 5 Set Training Mode Variables 9 17 Bootstrap resampl
9. e name of a file that has been fully scored alias a 1 by F cell array of strings that lists the aliases for the files listed in SCORER finished file current a struct with the following fields file a string with the name of the file that is currently being scored alias the alias assigned to the file that is currently being scored o RIPScoreVersion a string with the version of RIPScore that created this file Scoring results e g scored TEST ALIAS mat This file has the scoring details from an analysis performed by scorer TEST The term ALTAS in the file name corresponds to the alias of the scored file with name listed in SCORER finished file or SCORER current file This file contains the variables described next gt SCORING A struct with the detailed results from the manual analysis It has the following fields o NextScore an index indicating the number of segments scored S plus 1 o Events an S by 4 matrix with the RIP patterns assigned to each data segment The columns are 1 segment start time 2 segment end time 3 code of pattern assigned to the segment pause 1 asynchronous breathing 2 movement artifact 3 synchronous breathing 4 sigh 5 unknown 99 4 timestamp o Scorer a string with the scorer ID Comments a struct with comments that the scorer assigned to scored segments It has the following fields start aC by 1 vector with the start time of the segment linked to the comment
10. es to estimate standard deviations ALPHA for 1 4LPHA confidence intervals bot wL half the length in samples of the segment concatenation window see combineSignals 3 winType type of concatenation window see combineSignals Consecutive segments of each pattern type to finish E stage Segment proportion that has to be correctly identified to be considered detected in practice stage bs Maximum length in s of practice stage before starting the testing stage 600 Length in s of the testing stage 900 Effective training time inclusion threshold in s 20 Kappa threshold to advance level bs Effective training time threshold to advance level in 4400 canes This is only required if RIPScore is set to run in Training Mode just click OK for any other mode RIPScore will suggest the default values The variables are gt gt Bootstrap resamples This is an integer used to estimate standard deviations of kappa estimates ALPHA This is a real value in the open interval 0 1 used for computation of 1 ALPHA confidence intervals wL samples This is an integer with half the length of the segment concatenation window see function combineSignals for additional information winType This is an integer with the type of the concatenation window see function combineSignals for additional information 10 17 6 7 gt Consecutive segments This is an integer with t
11. he number of consecutive segments of each pattern type that are required to finish practice stage gt Segment proportion A real value in the interval 0 1 that indicates the proportion of a scored segment that has to match the Actual Pattern to be considered correct in practice stage gt Maximum length of practice stage s The maximum length of the practice stage before the start of the testing stage gt Length of the testing stage s The length of the testing stage gt Effective training time inclusion threshold s The maximum time difference between consecutive scored segments timestamps to be included in the calculation of effective training time gt Kappa threshold The minimum kappa required to advance from level 1 to level 2 gt Effective training time threshold to advance level s The maximum effective training time permitted when advancing from level 1 to level 2 Select the true pattern segment library file lol xl Select the true pattern segment library file This is only required if RIPScore is set to run in Training Mode click OK and then Esc for any other mode Choose the file containing the library of true pattern segments In the default configuration this file is C McCRIB Data POA TruePattern Segment _Library TruePattern Library mat After selecting the file RIPScore will output the full path to it lol x The true pattern segment library will be loaded fr
12. le contains the variables described next gt SCORING A struct with the detailed results from the manual analysis It has the following fields O NextScore an index indicating the number of segments scored S plus 1 o Events an S by 4 matrix with the patterns assigned to each data segment The columns are 1 segment start time 2 segment end time 3 code of pattern assigned to the segment pause 1 asynchronous breathing 2 movement artifact 3 synchronous breathing 4 sigh 5 unknown 99 4 timestamp o Scorer a string with the scorer ID Comments a struct with comments that the scorer assigned to scored segments It has the following fields start aC by 1 vector with the start time of the segment linked to the comment end a C by 1 vector with the end time of the segment linked to the comment eventID a C by 1 vector with the index of the linked segment as it appears in SCORING Events comment a 1 by C cell array with the comments assigned to the linked segments ElapsedTime deprecated o Completed a flag indicating whether this data record has been completely scored or not O FileName a string with the name of this file o RIPScoreVersion a string with the version of RIPScore that created this file o currentTime a scalar with the latest Epoch Start Time gt DATA A struct with the data used in this training session It has the following fields 000000 0 O RC an N by 1 vector with
13. om C McCRIBSD atas POAST ruePattern_Segment_Library TruePattern_Library mat Click OK RIPScore is now configured and will save a new cnf mat file in the application s main directory Jol x RIPScore has been configured To modify the configuration run RlPScore_setParameters or delete the file C McCRIB McCRIBS RIPSCORESRIPScorescnf mat and re load AlPScore 11 17 V Data Files This section describes the format of files used by RIPScore it is divided in input and output files A Input RIPScore reads cardiorespiratory data stored in MATLAB mat format An input file must have the following variable gt B data An N by 5 matrix with the recorded raw data The columns have the following signals 1 time s 2 ribcage a u 3 abdomen a u 4 photoplethysmography a u and 5 blood oxygen saturation Output RIPScore generates several files related to the training of scorers and their analyses The files are in MATLAB mat format The following list describes the contents of these files 1 Scorer data e g scorer TEST mat 2 This file has a summary of the files analyzed by scorer TEST The file contains the variables described next gt SCORER A struct with the following fields o finished a struct with a list of all files that have been completely scored It has the following fields file a 1 by F cell array of strings where each cell has th
14. rent session O finished 1 not finished fileSaved a string with the path and name of the latest SAVED version of the current training session fileBackup a string with the path and name of the latest BACKUP version of the current training session fileSelected a string with the path and name of the file selected to be loaded if there are both SAVED and BACKUP versions If there are neither SAVED nor BACKUP versions this variable is an empty string ConfusionMatrix a 2 by M cell array with estimates of the scorer s confusion matrix from each training session The first row corresponds to level 1 and the second to level 2 Each column corresponds to each session Each cell contains a 6 by 6 matrix where the rows correspond to the patterns assigned by the scorer and the columns to the actual pattern Col1 row1 Pause col2 row2 Asynchronous breathing col3 row3 Movement artifact col4 row4 Synchronous breathing col5 row5 Sigh col6 row6 Unknown o EffectiveTrainingTime a 1 by 2 cell array with the effective time in seconds required to complete the training session see 1 Col1 Level 1 Col2 Level2 Each cell is a 1 by M vector where M is the number of training sessions 0000 4 Training session results e g trained TEST level X iteration Y mat 14 17 This is a file with the scoring details from a training session of scorer TEST The name indicates that it corresponds to the y training session on level x The fi
15. ttern types col1 Pause col2 Asynchronous breathing col3 Movement artifact col4 Synchronous breathing col5 Sigh col6 Unknown kstd a 1 by M vector with the estimated standard deviation of kappa for the M training sessions RIPScore estimates standard deviations using the bootstrap method 4 kjstd an M by 6 vector with the estimates of pattern specific standard deviation of kappa for each of the M training sessions RIPScore estimates standard deviations using the bootstrap method Each column corresponds to one the 6 unique pattern types coll Pause col2 Asynchronous breathing col3 Movement artifact col4 Synchronous breathing col5 Sigh col6 Unknown kcil deprecated kcih deprecated kjcil deprecated kjcih deprecated IntraAgreement a 1 by 2 cell array with estimates of the consistency performance estimated using the Fleiss kappa statistic 2 3 in level 1 col1 and level 2 col2 Each cell is a struct array with the following fields k a1 by M vector with the kappa estimate from each of the M training sessions kj an M by 6 vector with the pattern specific kappa estimate from each of the M training sessions Each column corresponds to one the 6 unique pattern types col1 Pause col2 Asynchronous breathing col3 Movement artifact col4 Synchronous breathing col5 Sigh col6 Unknown 13 17 kstd a 1 by M vector with the estimated standard deviation of kappa for the M training sessions
16. wing disclaimer 2 Redistributions in binary form must reproduce the above copyright notice this list of conditions and the following disclaimer in the documentation and or other materials provided with the distribution THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT INDIRECT INCIDENTAL SPECIAL EXEMPLARY OR CONSEQUENTIAL DAMAGES INCLUDING BUT NOT LIMITED TO PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES LOSS OF USE DATA OR PROFITS OR BUSINESS INTERRUPTION HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY WHETHER IN CONTRACT STRICT LIABILITY OR TORT INCLUDING NEGLIGENCE OR OTHERWISE ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE 3 17 II Acknowledgement The development of RIPScore was supported in part by the Natural Sciences and Engineering Research Council of Canada The work of Carlos Alejandro Robles Rubio was supported in part by the Mexican National Council for Science and Technology and in part by the Queen Elizabeth Hospital of Montreal Foundation Chair in Pediatric Anesthesia Karen A Brown was supported in part by the Queen Elizabeth Hospital of Montreal Foundation Chair in Pediatric Anesthesia 4
Download Pdf Manuals
Related Search